Expert systems applied to spacecraft fire safety

NASA Technical Reports Server (NTRS)

Smith, Richard L.; Kashiwagi, Takashi

1989-01-01

Expert systems are problem-solving programs that combine a knowledge base and a reasoning mechanism to simulate a human expert. The development of an expert system to manage fire safety in spacecraft, in particular the NASA Space Station Freedom, is difficult but clearly advantageous in the long-term. Some needs in low-gravity flammability characteristics, ventilating-flow effects, fire detection, fire extinguishment, and decision models, all necessary to establish the knowledge base for an expert system, are discussed.

Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

NASA Technical Reports Server (NTRS)

Stephan, Amy; Erikson, Carol A.

1991-01-01

As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application.

Temporal logics and real time expert systems.

PubMed

Blom, J A

1996-10-01

This paper introduces temporal logics. Due to the eternal compromise between expressive adequacy and reasoning efficiency that must decided upon in any application, full (first order logic or modal logic based) temporal logics are frequently not suitable. This is especially true in real time expert systems, where a fixed (and usually small) response time must be guaranteed. One such expert system, Fagan's VM, is reviewed, and a delineation is given of how to formally describe and reason with time in medical protocols. It is shown that Petri net theory is a useful tool to check the correctness of formalised protocols.

An expert system for the design of heating, ventilating, and air-conditioning systems

NASA Astrophysics Data System (ADS)

Camejo, Pedro Jose

1989-12-01

Expert systems are computer programs that seek to mimic human reason. An expert system shelf, a software program commonly used for developing expert systems in a relatively short time, was used to develop a prototypical expert system for the design of heating, ventilating, and air-conditioning (HVAC) systems in buildings. Because HVAC design involves several related knowledge domains, developing an expert system for HVAC design requires the integration of several smaller expert systems known as knowledge bases. A menu program and several auxiliary programs for gathering data, completing calculations, printing project reports, and passing data between the knowledge bases are needed and have been developed to join the separate knowledge bases into one simple-to-use program unit.

Expert system for analyzing eddy current measurements

DOEpatents

Levy, Arthur J.; Oppenlander, Jane E.; Brudnoy, David M.; Englund, James M.; Loomis, Kent C.

1994-01-01

A method and apparatus (called DODGER) analyzes eddy current data for heat exchanger tubes or any other metallic object. DODGER uses an expert system to analyze eddy current data by reasoning with uncertainty and pattern recognition. The expert system permits DODGER to analyze eddy current data intelligently, and obviate operator uncertainty by analyzing the data in a uniform and consistent manner.

ART-Ada: An Ada-based expert system tool

NASA Technical Reports Server (NTRS)

Lee, S. Daniel; Allen, Bradley P.

1990-01-01

The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in an increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. The Automated Reasoning Tool-Ada (ART-Ada), an Ada expert system tool, is explained. ART-Ada allows applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom program and the U.S. Air Force.

ART-Ada: An Ada-based expert system tool

NASA Technical Reports Server (NTRS)

Lee, S. Daniel; Allen, Bradley P.

1991-01-01

The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. Automated Reasoning Tool (ART) Ada, an Ada Expert system tool is described. ART-Ada allow applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom Program and the U.S. Air Force.

Expert system for the design of heating, ventilating, and air-conditioning systems. Master's thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Camejo, P.J.

1989-12-01

Expert systems are computer programs that seek to mimic human reason. An expert system shelf, a software program commonly used for developing expert systems in a relatively short time, was used to develop a prototypical expert system for the design of heating, ventilating, and air-conditioning (HVAC) systems in buildings. Because HVAC design involves several related knowledge domains, developing an expert system for HVAC design requires the integration of several smaller expert systems known as knowledge bases. A menu program and several auxiliary programs for gathering data, completing calculations, printing project reports, and passing data between the knowledge bases are neededmore » and have been developed to join the separate knowledge bases into one simple-to-use program unit.« less

ECLIPS: An extended CLIPS for backward chaining and goal-directed reasoning

NASA Technical Reports Server (NTRS)

Homeier, Peter V.; Le, Thach C.

1991-01-01

Realistic production systems require an integrated combination of forward and backward reasoning to reflect appropriately the processes of natural human expert reasoning. A control mechanism that consists solely of forward reasoning is not an effective way to promptly focus the system's attention as calculation proceeds. Often, expert system programmers will attempt to compensate for this lack by using data to enforce the desired goal directed control structure. This approach is inherently flawed in that it is attempting to use data to fulfill the role of control. This paper will describe our implementation of backward chaining in C Language Integrated Production System (CLIPS), and show how this has shortened and simplified various CLIPS programs. This work was done at the Aerospace Corporation, and has general applicability.

ART-Ada design project, phase 2

NASA Technical Reports Server (NTRS)

Lee, S. Daniel; Allen, Bradley P.

1990-01-01

Interest in deploying expert systems in Ada has increased. An Ada based expert system tool is described called ART-Ada, which was built to support research into the language and methodological issues of expert systems in Ada. ART-Ada allows applications of an existing expert system tool called ART-IM (Automated Reasoning Tool for Information Management) to be deployed in various Ada environments. ART-IM, a C-based expert system tool, is used to generate Ada source code which is compiled and linked with an Ada based inference engine to produce an Ada executable image. ART-Ada is being used to implement several expert systems for NASA's Space Station Freedom Program and the U.S. Air Force.

Hydraulic Characteristics Of Two Bicycle-Safe Grate Inlet Designs

DOT National Transportation Integrated Search

1988-12-01

Expert Systems are computer programs designed to include a simulation of the reasoning and decision-making processes of human experts. This report provides a set of general guidelines for the development and distribution of highway related expert sys...

An Embedded Rule-Based Diagnostic Expert System in Ada

NASA Technical Reports Server (NTRS)

Jones, Robert E.; Liberman, Eugene M.

1992-01-01

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Benchmarking expert system tools

NASA Technical Reports Server (NTRS)

Riley, Gary

1988-01-01

As part of its evaluation of new technologies, the Artificial Intelligence Section of the Mission Planning and Analysis Div. at NASA-Johnson has made timing tests of several expert system building tools. Among the production systems tested were Automated Reasoning Tool, several versions of OPS5, and CLIPS (C Language Integrated Production System), an expert system builder developed by the AI section. Also included in the test were a Zetalisp version of the benchmark along with four versions of the benchmark written in Knowledge Engineering Environment, an object oriented, frame based expert system tool. The benchmarks used for testing are studied.

Enhancements to the Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Hofmann, Martin O.

1993-01-01

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Enhancements to the Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Hofmann, Martin O.

1993-01-01

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The result of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Evidential Reasoning in Expert Systems for Image Analysis.

DTIC Science & Technology

1985-02-01

techniques to image analysis (IA). There is growing evidence that these techniques offer significant improvements in image analysis , particularly in the...2) to provide a common framework for analysis, (3) to structure the ER process for major expert-system tasks in image analysis , and (4) to identify...approaches to three important tasks for expert systems in the domain of image analysis . This segment concluded with an assessment of the strengths

An overview of expert systems. [artificial intelligence

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1982-01-01

An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.

[Development of expert diagnostic system for common respiratory diseases].

PubMed

Xu, Wei-hua; Chen, You-ling; Yan, Zheng

2014-03-01

To develop an internet-based expert diagnostic system for common respiratory diseases. SaaS system was used to build architecture; pattern of forward reasoning was applied for inference engine design; ASP.NET with C# from the tool pack of Microsoft Visual Studio 2005 was used for website-interview medical expert system.The database of the system was constructed with Microsoft SQL Server 2005. The developed expert system contained large data memory and high efficient function of data interview and data analysis for diagnosis of various diseases.The users were able to perform this system to obtain diagnosis for common respiratory diseases via internet. The developed expert system may be used for internet-based diagnosis of various respiratory diseases,particularly in telemedicine setting.

Relying on experts as we reason together.

PubMed

Richardson, Henry S

2012-06-01

In various contexts, it is thought to be important that we reason together. For instance, an attractive conception of democracy requires that citizens reach lawmaking decisions by reasoning with one another. Reasoning requires that reasoners survey the considerations that they take to be reasons, proceed by a coherent train of thought, and reach conclusions freely. De facto reliance on experts threatens the possibility of collective reasoning by making some reasons collectively unsurveyable, raising questions about the coherence of the resulting train of thought. De jure reliance on experts threatens the possibility of collective reasoning by seeming to make some conclusions irreversible. The paper argues that collective reasoning that relies on experts would nonetheless be possible if the unsurveyable reasons "mesh," if the expert considerations are at least in principle publicly recoverable, and if de jure authority of expert decision is always subject to appeal.

Approximate reasoning using terminological models

NASA Technical Reports Server (NTRS)

Yen, John; Vaidya, Nitin

1992-01-01

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved.

SigmaCLIPSE = presentation management + NASA CLI PS + SQL

NASA Technical Reports Server (NTRS)

Weiss, Bernard P., Jr.

1990-01-01

SigmaCLIPSE provides an expert systems and 'intelligent' data base development program for diverse systems integration environments that require support for automated reasoning and expert systems technology, presentation management, and access to 'intelligent' SQL data bases. The SigmaCLIPSE technology and and its integrated ability to access 4th generation application development and decision support tools through a portable SQL interface, comprises a sophisticated software development environment for solving knowledge engineering and expert systems development problems in information intensive commercial environments -- financial services, health care, and distributed process control -- where the expert system must be extendable -- a major architectural advantage of NASA CLIPS. SigmaCLIPSE is a research effort intended to test the viability of merging SQL data bases with expert systems technology.

An SSME High Pressure Oxidizer Turbopump diagnostic system using G2 real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2 real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for the SSME. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach has been adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

An SSME high pressure oxidizer turbopump diagnostic system using G2(TM) real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2(TM) real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for Space Shuttle Main Engine. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach was adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

Passive acquisition of CLIPS rules

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1991-01-01

The automated acquisition of knowledge by machine has not lived up to expectations, and knowledge engineering remains a human intensive task. Part of the reason for the lack of success is the difference in the cognitive focus of the expert. The expert must shift his or her focus from the subject domain to that of the representation environment. In doing so this cognitive shift introduces opportunity for errors and omissions. Presented here is work that observes the expert interact with a simulation of the domain. The system logs changes in the simulation objects and the expert's actions in response to those changes. This is followed by the application of inductive reasoning to move the domain specific rules observed to general domain rules.

The nutrition advisor expert system

NASA Technical Reports Server (NTRS)

Huse, Scott M.; Shyne, Scott S.

1991-01-01

The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.

Expert systems tools for Hubble Space Telescope observation scheduling

NASA Technical Reports Server (NTRS)

Miller, Glenn; Rosenthal, Don; Cohen, William; Johnston, Mark

1987-01-01

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Reference standards, judges, and comparison subjects: roles for experts in evaluating system performance.

PubMed

Hripcsak, George; Wilcox, Adam

2002-01-01

Medical informatics systems are often designed to perform at the level of human experts. Evaluation of the performance of these systems is often constrained by lack of reference standards, either because the appropriate response is not known or because no simple appropriate response exists. Even when performance can be assessed, it is not always clear whether the performance is sufficient or reasonable. These challenges can be addressed if an evaluator enlists the help of clinical domain experts. 1) The experts can carry out the same tasks as the system, and then their responses can be combined to generate a reference standard. 2)The experts can judge the appropriateness of system output directly. 3) The experts can serve as comparison subjects with which the system can be compared. These are separate roles that have different implications for study design, metrics, and issues of reliability and validity. Diagrams help delineate the roles of experts in complex study designs.

A parallel strategy for implementing real-time expert systems using CLIPS

NASA Technical Reports Server (NTRS)

Ilyes, Laszlo A.; Villaseca, F. Eugenio; Delaat, John

1994-01-01

As evidenced by current literature, there appears to be a continued interest in the study of real-time expert systems. It is generally recognized that speed of execution is only one consideration when designing an effective real-time expert system. Some other features one must consider are the expert system's ability to perform temporal reasoning, handle interrupts, prioritize data, contend with data uncertainty, and perform context focusing as dictated by the incoming data to the expert system. This paper presents a strategy for implementing a real time expert system on the iPSC/860 hypercube parallel computer using CLIPS. The strategy takes into consideration not only the execution time of the software, but also those features which define a true real-time expert system. The methodology is then demonstrated using a practical implementation of an expert system which performs diagnostics on the Space Shuttle Main Engine (SSME). This particular implementation uses an eight node hypercube to process ten sensor measurements in order to simultaneously diagnose five different failure modes within the SSME. The main program is written in ANSI C and embeds CLIPS to better facilitate and debug the rule based expert system.

Reference Standards, Judges, and Comparison Subjects

PubMed Central

Hripcsak, George; Wilcox, Adam

2002-01-01

Medical informatics systems are often designed to perform at the level of human experts. Evaluation of the performance of these systems is often constrained by lack of reference standards, either because the appropriate response is not known or because no simple appropriate response exists. Even when performance can be assessed, it is not always clear whether the performance is sufficient or reasonable. These challenges can be addressed if an evaluator enlists the help of clinical domain experts. 1) The experts can carry out the same tasks as the system, and then their responses can be combined to generate a reference standard. 2)The experts can judge the appropriateness of system output directly. 3) The experts can serve as comparison subjects with which the system can be compared. These are separate roles that have different implications for study design, metrics, and issues of reliability and validity. Diagrams help delineate the roles of experts in complex study designs. PMID:11751799

Robotic air vehicle. Blending artificial intelligence with conventional software

NASA Technical Reports Server (NTRS)

Mcnulty, Christa; Graham, Joyce; Roewer, Paul

1987-01-01

The Robotic Air Vehicle (RAV) system is described. The program's objectives were to design, implement, and demonstrate cooperating expert systems for piloting robotic air vehicles. The development of this system merges conventional programming used in passive navigation with Artificial Intelligence techniques such as voice recognition, spatial reasoning, and expert systems. The individual components of the RAV system are discussed as well as their interactions with each other and how they operate as a system.

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark J.

1991-01-01

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

Ground terminal expert (GTEX). Part 2: Expert system diagnostics for a 30/20 Gigahertz satellite transponder

NASA Technical Reports Server (NTRS)

Durkin, John; Schlegelmilch, Richard; Tallo, Donald

1992-01-01

A research effort was undertaken to investigate how expert system technology could be applied to a satellite communications system. The focus of the expert system is the satellite earth station. A proof of concept expert system called the Ground Terminal Expert (GTEX) was developed at the University of Akron in collaboration with the NASA Lewis Research Center. With the increasing demand for satellite earth stations, maintenance is becoming a vital issue. Vendors of such systems will be looking for cost effective means of maintaining such systems. The objective of GTEX is to aid in diagnosis of faults occurring with the digital earth station. GTEX was developed on a personal computer using the Automated Reasoning Tool for Information Management (ART-IM) developed by the Inference Corporation. Developed for the Phase 2 digital earth station, GTEX is a part of the Systems Integration Test and Evaluation (SITE) facility located at the NASA Lewis Research Center.

A parallel expert system for the control of a robotic air vehicle

NASA Technical Reports Server (NTRS)

Shakley, Donald; Lamont, Gary B.

1988-01-01

Expert systems can be used to govern the intelligent control of vehicles, for example the Robotic Air Vehicle (RAV). Due to the nature of the RAV system the associated expert system needs to perform in a demanding real-time environment. The use of a parallel processing capability to support the associated expert system's computational requirement is critical in this application. Thus, algorithms for parallel real-time expert systems must be designed, analyzed, and synthesized. The design process incorporates a consideration of the rule-set/face-set size along with representation issues. These issues are looked at in reference to information movement and various inference mechanisms. Also examined is the process involved with transporting the RAV expert system functions from the TI Explorer, where they are implemented in the Automated Reasoning Tool (ART), to the iPSC Hypercube, where the system is synthesized using Concurrent Common LISP (CCLISP). The transformation process for the ART to CCLISP conversion is described. The performance characteristics of the parallel implementation of these expert systems on the iPSC Hypercube are compared to the TI Explorer implementation.

Integration of perception and reasoning in fast neural modules

NASA Technical Reports Server (NTRS)

Fritz, David G.

1989-01-01

Artificial neural systems promise to integrate symbolic and sub-symbolic processing to achieve real time control of physical systems. Two potential alternatives exist. In one, neural nets can be used to front-end expert systems. The expert systems, in turn, are developed with varying degrees of parallelism, including their implementation in neural nets. In the other, rule-based reasoning and sensor data can be integrated within a single hybrid neural system. The hybrid system reacts as a unit to provide decisions (problem solutions) based on the simultaneous evaluation of data and rules. Discussed here is a model hybrid system based on the fuzzy cognitive map (FCM). The operation of the model is illustrated with the control of a hypothetical satellite that intelligently alters its attitude in space in response to an intersecting micrometeorite shower.

Expert systems for MSFC power systems

NASA Technical Reports Server (NTRS)

Weeks, David J.

1988-01-01

Future space vehicles and platforms including Space Station will possess complex power systems. These systems will require a high level of autonomous operation to allow the crew to concentrate on mission activities and to limit the number of ground support personnel to a reasonable number. The Electrical Power Branch at NASA-Marshall is developing advanced automation approaches which will enable the necessary levels of autonomy. These approaches include the utilization of knowledge based or expert systems.

Decision support system and medical liability.

PubMed Central

Allaërt, F. A.; Dusserre, L.

1992-01-01

Expert systems, which are going to be an essential tool in Medicine, are evolving in terms of sophistication of both knowledge representation and types of reasoning models used. The more efficient they are, the more often they will be used and professional liability will be involved. So after giving a short survey of configuration and working of expert systems, the authors will study the liabilities of people building and the using expert systems regarding some various dysfunctions. Of course the expert systems have to be considered only for human support and they should not possess any authority themselves, therefore the doctors must keep in mind that it is their own responsibility and as such keep their judgment and criticism. However other professionals could be involved, if they have participated in the building of expert systems. The different liabilities and the burden of proof are discussed according to some possible dysfunctions. In any case the final proof is inside the expert system by itself through re-computation of data. PMID:1482972

CLIPS/Ada: An Ada-based tool for building expert systems

NASA Technical Reports Server (NTRS)

White, W. A.

1990-01-01

Clips/Ada is a production system language and a development environment. It is functionally equivalent to the CLIPS tool. CLIPS/Ada was developed in order to provide a means of incorporating expert system technology into projects where the use of the Ada language had been mandated. A secondary purpose was to glean information about the Ada language and its compilers. Specifically, whether or not the language and compilers were mature enough to support AI applications. The CLIPS/Ada tool is coded entirely in Ada and is designed to be used by Ada systems that require expert reasoning.

An approach to combining heuristic and qualitative reasoning in an expert system

NASA Technical Reports Server (NTRS)

Jiang, Wei-Si; Han, Chia Yung; Tsai, Lian Cheng; Wee, William G.

1988-01-01

An approach to combining the heuristic reasoning from shallow knowledge and the qualitative reasoning from deep knowledge is described. The shallow knowledge is represented in production rules and under the direct control of the inference engine. The deep knowledge is represented in frames, which may be put in a relational DataBase Management System. This approach takes advantage of both reasoning schemes and results in improved efficiency as well as expanded problem solving ability.

Space applications of artificial intelligence; Proceedings of the Annual Goddard Conference, Greenbelt, MD, May 16, 17, 1989

NASA Technical Reports Server (NTRS)

Rash, James L. (Editor); Dent, Carolyn P. (Editor)

1989-01-01

Theoretical and implementation aspects of AI systems for space applications are discussed in reviews and reports. Sections are devoted to planning and scheduling, fault isolation and diagnosis, data management, modeling and simulation, and development tools and methods. Particular attention is given to a situated reasoning architecture for space repair and replace tasks, parallel plan execution with self-processing networks, the electrical diagnostics expert system for Spacelab life-sciences experiments, diagnostic tolerance for missing sensor data, the integration of perception and reasoning in fast neural modules, a connectionist model for dynamic control, and applications of fuzzy sets to the development of rule-based expert systems.

A Logical Framework for Service Migration Based Survivability

DTIC Science & Technology

2016-06-24

platforms; Service Migration Strategy Fuzzy Inference System Knowledge Base Fuzzy rules representing domain expert knowledge about implications of...service migration strategy. Our approach uses expert knowledge as linguistic reasoning rules and takes service programs damage assessment, service...programs complexity, and available network capability as input. The fuzzy inference system includes four components as shown in Figure 5: (1) a knowledge

Knowledge representation by connection matrices: A method for the on-board implementation of large expert systems

NASA Technical Reports Server (NTRS)

Kellner, A.

1987-01-01

Extremely large knowledge sources and efficient knowledge access characterizing future real-life artificial intelligence applications represent crucial requirements for on-board artificial intelligence systems due to obvious computer time and storage constraints on spacecraft. A type of knowledge representation and corresponding reasoning mechanism is proposed which is particularly suited for the efficient processing of such large knowledge bases in expert systems.

Development of nickel hydrogen battery expert system

NASA Technical Reports Server (NTRS)

Shiva, Sajjan G.

1990-01-01

The Hubble Telescope Battery Testbed employs the nickel-cadmium battery expert system (NICBES-2) which supports the evaluation of performances of Hubble Telescope spacecraft batteries and provides alarm diagnosis and action advice. NICBES-2 also provides a reasoning system along with a battery domain knowledge base to achieve this battery health management function. An effort to modify NICBES-2 to accommodate nickel-hydrogen battery environment in testbed is described.

Expert Witness: A system for developing expert medical testimony

NASA Technical Reports Server (NTRS)

Lewandowski, Raymond; Perkins, David; Leasure, David

1994-01-01

Expert Witness in an expert system designed to assist attorneys and medical experts in determining the merit of medical malpractice claims in the area of obstetrics. It substitutes the time of the medical expert with the time of a paralegal assistant guided by the expert system during the initial investigation of the medical records and patient interviews. The product of the system is a narrative transcript containing important data, immediate conclusions from the data, and overall conclusions of the case that the attorney and medical expert use to make decisions about whether and how to proceed with the case. The transcript may also contain directives for gathering additional information needed for the case. The system is a modified heuristic classifier and is implemented using over 600 CLIPS rules together with a C-based user interface. The data abstraction and solution refinement are implemented directly using forward chaining production and matching. The use of CLIPS and C is essential to delivering a system that runs on a generic PC platform. The direct implementation in CLIPS together with locality of inference ensures that the system will scale gracefully. Two years of use has revealed no errors in the reasoning.

Expert system shell to reason on large amounts of data

NASA Technical Reports Server (NTRS)

Giuffrida, Gionanni

1994-01-01

The current data base management systems (DBMS's) do not provide a sophisticated environment to develop rule based expert systems applications. Some of the new DBMS's come with some sort of rule mechanism; these are active and deductive database systems. However, both of these are not featured enough to support full implementation based on rules. On the other hand, current expert system shells do not provide any link with external databases. That is, all the data are kept in the system working memory. Such working memory is maintained in main memory. For some applications the reduced size of the available working memory could represent a constraint for the development. Typically these are applications which require reasoning on huge amounts of data. All these data do not fit into the computer main memory. Moreover, in some cases these data can be already available in some database systems and continuously updated while the expert system is running. This paper proposes an architecture which employs knowledge discovering techniques to reduce the amount of data to be stored in the main memory; in this architecture a standard DBMS is coupled with a rule-based language. The data are stored into the DBMS. An interface between the two systems is responsible for inducing knowledge from the set of relations. Such induced knowledge is then transferred to the rule-based language working memory.

Design and implementation of a status at a glance user interface for a power distribution expert system

NASA Technical Reports Server (NTRS)

Liberman, Eugene M.; Manner, David B.; Dolce, James L.; Mellor, Pamela A.

1993-01-01

Expert systems are widely used in health monitoring and fault detection applications. One of the key features of an expert system is that it possesses a large body of knowledge about the application for which it was designed. When the user consults this knowledge base, it is essential that the expert system's reasoning process and its conclusions be as concise as possible. If, in addition, an expert system is part of a process monitoring system, the expert system's conclusions must be combined with current events of the process. Under these circumstances, it is difficult for a user to absorb and respond to all the available information. For example, a user can become distracted and confused if two or more unrelated devices in different parts of the system require attention. A human interface designed to integrate expert system diagnoses with process data and to focus the user's attention to the important matters provides a solution to the 'information overload' problem. This paper will discuss a user interface to the power distribution expert system for Space Station Freedom. The importance of features which simplify assessing system status and which minimize navigating through layers of information will be discussed. Design rationale and implementation choices will also be presented.

Simple explanations and reasoning: From philosophy of science to expert systems

NASA Technical Reports Server (NTRS)

Rochowiak, Daniel

1988-01-01

A preliminary prototype of a simple explanation system was constructed. Although the system, based on the idea of storytelling, did not incorporate all of the principles of simple explanation, it did demonstrate the potential of the approach. The system incorporated a hypertext system, an inference engine, and facilities for constructing contrast type explanations. The continued development of such a system should prove to be valuable. By extending the resources of the expert system paradigm, the knowledge engineer is not forced to learn a new set of skills, and the domain knowledge already acquired by him is not lost. Further, both the beginning user and the more advanced user can be accommodated. For the beginning user, corrective explanations and ES explanations provide facilities for more clearly understanding the way in which the system is functioning. For the more advanced user, the instance and state explanations allow him to focus on the issues at hand. The simple model of explanation attempts to exploit and show how the why and how facilities of the expert system paradigm can be extended by attending to the pragmatics of explanation and adding texture to the ordinary pattern of reasoning in a rule based system.

An intelligent user interface for browsing satellite data catalogs

NASA Technical Reports Server (NTRS)

Cromp, Robert F.; Crook, Sharon

1989-01-01

A large scale domain-independent spatial data management expert system that serves as a front-end to databases containing spatial data is described. This system is unique for two reasons. First, it uses spatial search techniques to generate a list of all the primary keys that fall within a user's spatial constraints prior to invoking the database management system, thus substantially decreasing the amount of time required to answer a user's query. Second, a domain-independent query expert system uses a domain-specific rule base to preprocess the user's English query, effectively mapping a broad class of queries into a smaller subset that can be handled by a commercial natural language processing system. The methods used by the spatial search module and the query expert system are explained, and the system architecture for the spatial data management expert system is described. The system is applied to data from the International Ultraviolet Explorer (IUE) satellite, and results are given.

Fuzzy associative memories

NASA Technical Reports Server (NTRS)

Kosko, Bart

1991-01-01

Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.

Expert Causal Reasoning and Explanation.

ERIC Educational Resources Information Center

Kuipers, Benjamin

The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

NASA Astrophysics Data System (ADS)

Xu, Bing; Liu, Liqun

To conquer the bottleneck problems existing in the traditional rule-based reasoning diseases diagnosis system, such as low reasoning efficiency and lack of flexibility, etc.. It researched the integrated case-based reasoning (CBR) and rule-based reasoning (RBR) technology, and put forward a litchi diseases diagnosis expert system (LDDES) with integrated reasoning method. The method use data mining and knowledge obtaining technology to establish knowledge base and case library. It adopt rules to instruct the retrieval and matching for CBR, and use association rule and decision trees algorithm to calculate case similarity.The experiment shows that the method can increase the system's flexibility and reasoning ability, and improve the accuracy of litchi diseases diagnosis.

CRN5EXP: Expert system for statistical quality control

NASA Technical Reports Server (NTRS)

Hentea, Mariana

1991-01-01

The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.

An application of object-oriented knowledge representation to engineering expert systems

NASA Technical Reports Server (NTRS)

Logie, D. S.; Kamil, H.; Umaretiya, J. R.

1990-01-01

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

Expert Recommender: Designing for a Network Organization

NASA Astrophysics Data System (ADS)

Reichling, Tim; Veith, Michael; Wulf, Volker

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge- intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.

Space Transportation System Meteorological Expert

NASA Technical Reports Server (NTRS)

Beller, Arthur E.; Stafford, Sue P.

1987-01-01

The STS Meteorological Expert (STSMET) is a long-term project to acquire general Shuttle operational weather forecasting expertise specific to the launch locale, to apply it to Shuttle operational weather forecasting tasks at the Cape Canaveral Forecast Facility, and ultimately to provide an on-line real-time operational aid to the duty forecasters in performing their tasks. Particular attention is given to the development of an approach called scenario-based reasoning, with specific application to summer thunderstorms; this type of reasoning can also be applied to frontal weather phenomena, visibility including fog, and wind shear.

Common sense reasoning about petroleum flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenberg, S.

1981-02-01

This paper describes an expert system for understanding and Reasoning in a petroleum resources domain. A basic model is implemented in FRL (Frame Representation Language). Expertise is encoded as rule frames. The model consists of a set of episodic contexts which are sequentially generated over time. Reasoning occurs in separate reasoning contexts consisting of a buffer frame and packets of rules. These function similar to small production systems. reasoning is linked to the model through an interface of Sentinels (instance driven demons) which notice anomalous conditions. Heuristics and metaknowledge are used through the creation of further reasoning contexts which overlaymore » the simpler ones.« less

Temporal and contextual knowledge in model-based expert systems

NASA Technical Reports Server (NTRS)

Toth-Fejel, Tihamer; Heher, Dennis

1987-01-01

A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.

Parallel processing and expert systems

NASA Technical Reports Server (NTRS)

Lau, Sonie; Yan, Jerry C.

1991-01-01

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited.

Bibliography: Artificial Intelligence.

ERIC Educational Resources Information Center

Smith, Richard L.

1986-01-01

Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

PVEX: An expert system for producibility/value engineering

NASA Technical Reports Server (NTRS)

Lam, Chun S.; Moseley, Warren

1991-01-01

PVEX is described as an expert system that solves the problem of selection of the material and process in missile manufacturing. The producibility and the value problem has been deeply studied in the past years, and was written in dBase III and PROLOG before. A new approach is presented in that the solution is achieved by introducing hypothetical reasoning, heuristic criteria integrated with a simple hypertext system and shell programming. PVEX combines KMS with Unix scripts which graphically depicts decision trees. The decision trees convey high level qualitative problem solving knowledge to users, and a stand-alone help facility and technical documentation is available through KMS. The system developed is considerably less development costly than any other comparable expert system.

Design and implementation of a status at a glance user interface for a power distribution expert system

NASA Technical Reports Server (NTRS)

Liberman, Eugene M.; Manner, David B.; Dolce, James L.; Mellor, Pamela A.

1993-01-01

A user interface to the power distribution expert system for Space Station Freedom is discussed. The importance of features which simplify assessing system status and which minimize navigating through layers of information are examined. Design rationale and implementation choices are also presented. The amalgamation of such design features as message linking arrows, reduced information content screens, high salience anomaly icons, and color choices with failure detection and diagnostic explanation from an expert system is shown to provide an effective status-at-a-glance monitoring system for power distribution. This user interface design offers diagnostic reasoning without compromising the monitoring of current events. The display can convey complex concepts in terms that are clear to its users.

An Expert System For Tuning Particle-Beam Accelerators

NASA Astrophysics Data System (ADS)

Lager, Darrel L.; Brand, Hal R.; Maurer, William J.; Searfus, Robert M.; Hernandez, Jose E.

1989-03-01

We have developed a proof-of-concept prototype of an expert system for tuning particle beam accelerators. It is designed to function as an intelligent assistant for an operator. In its present form it implements the strategies and reasoning followed by the operator for steering through the beam transport section of the Advanced Test Accelerator at Lawrence Livermore Laboratory's Site 300. The system is implemented in the language LISP using the Artificial Intelligence concepts of frames, daemons, and a representation we developed called a Monitored Decision Script.

"Expert" Verification of Classroom-Based Indicators of Teaching and Learning Effectiveness for Professional Renewable Certification.

ERIC Educational Resources Information Center

Naik, Nitin S.; And Others

The results are provided of a statewide content verification survey of "expert" educators designed to verify indicators in the 1989-90 System for Teaching and Learning Assessment and Review (STAR) as reasonable expectations for beginning and/or experienced teachers (BETs) in Louisiana and as providing professional endorsement at the…

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

NASA Technical Reports Server (NTRS)

Glass, B. J. (Editor)

1992-01-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Thermal Expert System (TEXSYS): Systems automony demonstration project, volume 1. Overview

NASA Technical Reports Server (NTRS)

Glass, B. J. (Editor)

1992-01-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS test bed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

NASA Astrophysics Data System (ADS)

Glass, B. J.

1992-10-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

An autonomous fault detection, isolation, and recovery system for a 20-kHz electric power distribution test bed

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Walters, Jerry L.

1991-01-01

Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed.

Model-Based Reasoning in the Detection of Satellite Anomalies

DTIC Science & Technology

1990-12-01

Conference on Artificial Intellegence . 1363-1368. Detroit, Michigan, August 89. Chu, Wei-Hai. "Generic Expert System Shell for Diagnostic Reasoning... Intellegence . 1324-1330. Detroit, Michigan, August 89. de Kleer, Johan and Brian C. Williams. "Diagnosing Multiple Faults," Artificial Intellegence , 32(1): 97...Benjamin Kuipers. "Model-Based Monitoring of Dynamic Systems," Proceedings of the Eleventh Intematianal Joint Conference on Artificial Intellegence . 1238

Computer Science and Statistics. Proceedings of the Symposium on the Interface (18th) Held on March 19-21, 1986 in Fort Collins, Colorado.

DTIC Science & Technology

1987-08-26

example, expert systems research would benefit examples are the Acute Renal Failure [15] system, the if it could attract statisticians to assist in...research projects including the Acute Renal Failure [15] system, the 6. EXPLAINING COMPLEX REASONING INTERNIST-] [22] system for diagnosis within the...the MEDAS and Acute Renal Failure systems. task at any point in reasoning about a case is constrained to Entropy-discriminate makes use of a measure

An intelligent tutoring system for space shuttle diagnosis

NASA Technical Reports Server (NTRS)

Johnson, William B.; Norton, Jeffrey E.; Duncan, Phillip C.

1988-01-01

An Intelligent Tutoring System (ITS) transcends conventional computer-based instruction. An ITS is capable of monitoring and understanding student performance thereby providing feedback, explanation, and remediation. This is accomplished by including models of the student, the instructor, and the expert technician or operator in the domain of interest. The space shuttle fuel cell is the technical domain for the project described below. One system, Microcomputer Intelligence for Technical Training (MITT), demonstrates that ITS's can be developed and delivered, with a reasonable amount of effort and in a short period of time, on a microcomputer. The MITT system capitalizes on the diagnostic training approach called Framework for Aiding the Understanding of Logical Troubleshooting (FAULT) (Johnson, 1987). The system's embedded procedural expert was developed with NASA's C-Language Integrated Production (CLIP) expert system shell (Cubert, 1987).

The Impact of Selected Contextual Factors on Experts' Clinical Reasoning Performance (Does Context Impact Clinical Reasoning Performance in Experts?)

ERIC Educational Resources Information Center

Durning, Steven J.; Artino, Anthony R.; Boulet, John R.; Dorrance, Kevin; van der Vleuten, Cees; Schuwirth, Lambert

2012-01-01

Context specificity, or the variation in a participant's performance from one case, or situation, to the next, is a recognized problem in medical education. However, studies have not explored the potential reasons for context specificity in experts using the lens of situated cognition and cognitive load theories (CLT). Using these theories, we…

Deciding alternative left turn signal phases using expert systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, E.C.P.

1988-01-01

The Texas Transportation Institute (TTI) conducted a study to investigate the feasibility of applying artificial intelligence (AI) technology and expert systems (ES) design concepts to a traffic engineering problem. Prototype systems were developed to analyze user input, evaluate various reasoning, and suggest suitable left turn phase treatment. These systems were developed using AI programming tools on IBM PC/XT/AT-compatible microcomputers. Two slightly different systems were designed using AI languages; another was built with a knowledge engineering tool. These systems include the PD PROLOG and TURBO PROLOG AI programs, as well as the INSIGHT Production Rule Language.

An Ada Based Expert System for the Ada Version of SAtool II. Volume 1 and 2

DTIC Science & Technology

1991-06-06

Integrated Computer-Aided Manufacturing (ICAM) (20). In fact, IDEF 0 stands for ICAM Definition Method Zero . IDEF0 defines a subset of SA that omits...reasoning that has been programmed). An expert’s knowledge is specific to one problem domain as opposed to knowledge about general problem-solving...techniques. General problem domains are medicine, finance, science or engineering and so forth in which an expert can solve specific problems very well

Test and Evaluation for Enhanced Security: A Quantitative Method to Incorporate Expert Knowledge into Test Planning Decisions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rizzo, Davinia; Blackburn, Mark

Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper coversmore » the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).« less

Boilermodel: A Qualitative Model-Based Reasoning System Implemented in Ada

DTIC Science & Technology

1991-09-01

comple- ment to shipboard engineering training. Accesion For NTIS CRA&I DTIO I A3 f_- Unairmoui1ccd [i Justification By ................... Distribut;or, I...investment (in terms of man-hours lost, equipment maintenance, materials, etc.) for initial training. On- going training is also required to sustain a...REASONING FROM MODELS Model-based expert systems have been written in many languages and for many different architectures . Knowledge representation also

An Investigation and Interpretation of Selected Topics in Uncertainty Reasoning

DTIC Science & Technology

1989-12-01

Characterizing seconditry uncertainty as spurious evidence and including it in the inference process , It was shown that probability ratio graphs are a...in the inference process has great impact on the computational complexity of an Inference process . viii An Investigation and Interpretation of...Systems," he outlines a five step process that incorporates Blyeslan reasoning in the development of the expert system rule base: 1. A group of

Intelligent fault isolation and diagnosis for communication satellite systems

NASA Technical Reports Server (NTRS)

Tallo, Donald P.; Durkin, John; Petrik, Edward J.

1992-01-01

Discussed here is a prototype diagnosis expert system to provide the Advanced Communication Technology Satellite (ACTS) System with autonomous diagnosis capability. The system, the Fault Isolation and Diagnosis EXpert (FIDEX) system, is a frame-based system that uses hierarchical structures to represent such items as the satellite's subsystems, components, sensors, and fault states. This overall frame architecture integrates the hierarchical structures into a lattice that provides a flexible representation scheme and facilitates system maintenance. FIDEX uses an inexact reasoning technique based on the incrementally acquired evidence approach developed by Shortliffe. The system is designed with a primitive learning ability through which it maintains a record of past diagnosis studies.

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

PubMed

Tsopra, R; Venot, A; Duclos, C

2014-01-01

Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties. The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs.

A failure management prototype: DR/Rx

NASA Technical Reports Server (NTRS)

Hammen, David G.; Baker, Carolyn G.; Kelly, Christine M.; Marsh, Christopher A.

1991-01-01

This failure management prototype performs failure diagnosis and recovery management of hierarchical, distributed systems. The prototype, which evolved from a series of previous prototypes following a spiral model for development, focuses on two functions: (1) the diagnostic reasoner (DR) performs integrated failure diagnosis in distributed systems; and (2) the recovery expert (Rx) develops plans to recover from the failure. Issues related to expert system prototype design and the previous history of this prototype are discussed. The architecture of the current prototype is described in terms of the knowledge representation and functionality of its components.

A Clinical Reasoning Tool for Virtual Patients: Design-Based Research Study.

PubMed

Hege, Inga; Kononowicz, Andrzej A; Adler, Martin

2017-11-02

Clinical reasoning is a fundamental process medical students have to learn during and after medical school. Virtual patients (VP) are a technology-enhanced learning method to teach clinical reasoning. However, VP systems do not exploit their full potential concerning the clinical reasoning process; for example, most systems focus on the outcome and less on the process of clinical reasoning. Keeping our concept grounded in a former qualitative study, we aimed to design and implement a tool to enhance VPs with activities and feedback, which specifically foster the acquisition of clinical reasoning skills. We designed the tool by translating elements of a conceptual clinical reasoning learning framework into software requirements. The resulting clinical reasoning tool enables learners to build their patient's illness script as a concept map when they are working on a VP scenario. The student's map is compared with the experts' reasoning at each stage of the VP, which is technically enabled by using Medical Subject Headings, which is a comprehensive controlled vocabulary published by the US National Library of Medicine. The tool is implemented using Web technologies, has an open architecture that enables its integration into various systems through an open application program interface, and is available under a Massachusetts Institute of Technology license. We conducted usability tests following a think-aloud protocol and a pilot field study with maps created by 64 medical students. The results show that learners interact with the tool but create less nodes and connections in the concept map than an expert. Further research and usability tests are required to analyze the reasons. The presented tool is a versatile, systematically developed software component that specifically supports the clinical reasoning skills acquisition. It can be plugged into VP systems or used as stand-alone software in other teaching scenarios. The modular design allows an extension with new feedback mechanisms and learning analytics algorithms. ©Inga Hege, Andrzej A Kononowicz, Martin Adler. Originally published in JMIR Medical Education (http://mededu.jmir.org), 02.11.2017.

Expert nurses' clinical reasoning under uncertainty: representation, structure, and process.

PubMed Central

Fonteyn, M. E.; Grobe, S. J.

1992-01-01

How do expert nurses reason when planning care and making clinical decisions for a patient who is at risk, and whose outcome is uncertain? In this study, a case study involving a critically ill elderly woman whose condition deteriorated over time, was presented in segments to ten expert critical care nurses. Think aloud method was used to elicit knowledge from these experts to provide conceptual information about their knowledge and to reveal their reasoning processes and problem-solving strategies. The verbatim transcripts were then analyzed using a systematic three-step method that makes analysis easier and adds creditability to study findings by providing a means of retracing and explaining analysis results. Findings revealed information about how patient problems were represented during reasoning, the manner in which experts subjects structured their plan of care, and the reasoning processes and heuristics they used to formulate solutions for resolving the patient's problems and preventing deterioration in the patient's condition. PMID:1482907

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Design a Fuzzy Rule-based Expert System to Aid Earlier Diagnosis of Gastric Cancer.

PubMed

Safdari, Reza; Arpanahi, Hadi Kazemi; Langarizadeh, Mostafa; Ghazisaiedi, Marjan; Dargahi, Hossein; Zendehdel, Kazem

2018-01-01

Screening and health check-up programs are most important sanitary priorities, that should be undertaken to control dangerous diseases such as gastric cancer that affected by different factors. More than 50% of gastric cancer diagnoses are made during the advanced stage. Currently, there is no systematic approach for early diagnosis of gastric cancer. to develop a fuzzy expert system that can identify gastric cancer risk levels in individuals. This system was implemented in MATLAB software, Mamdani inference technique applied to simulate reasoning of experts in the field, a total of 67 fuzzy rules extracted as a rule-base based on medical expert's opinion. 50 case scenarios were used to evaluate the system, the information of case reports is given to the system to find risk level of each case report then obtained results were compared with expert's diagnosis. Results revealed that sensitivity was 92.1% and the specificity was 83.1%. The results show that is possible to develop a system that can identify High risk individuals for gastric cancer. The system can lead to earlier diagnosis, this may facilitate early treatment and reduce gastric cancer mortality rate.

Software Analyzes Complex Systems in Real Time

NASA Technical Reports Server (NTRS)

2008-01-01

Expert system software programs, also known as knowledge-based systems, are computer programs that emulate the knowledge and analytical skills of one or more human experts, related to a specific subject. SHINE (Spacecraft Health Inference Engine) is one such program, a software inference engine (expert system) designed by NASA for the purpose of monitoring, analyzing, and diagnosing both real-time and non-real-time systems. It was developed to meet many of the Agency s demanding and rigorous artificial intelligence goals for current and future needs. NASA developed the sophisticated and reusable software based on the experience and requirements of its Jet Propulsion Laboratory s (JPL) Artificial Intelligence Research Group in developing expert systems for space flight operations specifically, the diagnosis of spacecraft health. It was designed to be efficient enough to operate in demanding real time and in limited hardware environments, and to be utilized by non-expert systems applications written in conventional programming languages. The technology is currently used in several ongoing NASA applications, including the Mars Exploration Rovers and the Spacecraft Health Automatic Reasoning Pilot (SHARP) program for the diagnosis of telecommunication anomalies during the Neptune Voyager Encounter. It is also finding applications outside of the Space Agency.

Computer Software for Intelligent Systems.

ERIC Educational Resources Information Center

Lenat, Douglas B.

1984-01-01

Discusses the development and nature of computer software for intelligent systems, indicating that the key to intelligent problem-solving lies in reducing the random search for solutions. Formal reasoning methods, expert systems, and sources of power in problem-solving are among the areas considered. Specific examples of such software are…

Reasoning and Data Representation in a Health and Lifestyle Support System.

PubMed

Hanke, Sten; Kreiner, Karl; Kropf, Johannes; Scase, Marc; Gossy, Christian

2017-01-01

Case-based reasoning and data interpretation is an artificial intelligence approach that capitalizes on past experience to solve current problems and this can be used as a method for practical intelligent systems. Case-based data reasoning is able to provide decision support for experts and clinicians in health systems as well as lifestyle systems. In this project we were focusing on developing a solution for healthy ageing considering daily activities, nutrition as well as cognitive activities. The data analysis of the reasoner followed state of the art guidelines from clinical practice. Guidelines provide a general framework to guide clinicians, and require consequent background knowledge to become operational, which is precisely the kind of information recorded in practice cases; cases complement guidelines very well and helps to interpret them. It is expected that the interest in case-based reasoning systems in the health.

Diagnosis: Reasoning from first principles and experiential knowledge

NASA Technical Reports Server (NTRS)

Williams, Linda J. F.; Lawler, Dennis G.

1987-01-01

Completeness, efficiency and autonomy are requirements for suture diagnostic reasoning systems. Methods for automating diagnostic reasoning systems include diagnosis from first principles (i.e., reasoning from a thorough description of structure and behavior) and diagnosis from experiential knowledge (i.e., reasoning from a set of examples obtained from experts). However, implementation of either as a single reasoning method fails to meet these requirements. The approach of combining reasoning from first principles and reasoning from experiential knowledge does address the requirements discussed above and can possibly ease some of the difficulties associated with knowledge acquisition by allowing developers to systematically enumerate a portion of the knowledge necessary to build the diagnosis program. The ability to enumerate knowledge systematically facilitates defining the program's scope, completeness, and competence and assists in bounding, controlling, and guiding the knowledge acquisition process.

ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems

NASA Technical Reports Server (NTRS)

Pachura, David W.; Suleiman, Salem A.; Mendler, Andrew P.

1988-01-01

ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems.

Adaptive control with an expert system based supervisory level. Thesis

NASA Technical Reports Server (NTRS)

Sullivan, Gerald A.

1991-01-01

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Dynamic reasoning in a knowledge-based system

NASA Technical Reports Server (NTRS)

Rao, Anand S.; Foo, Norman Y.

1988-01-01

Any space based system, whether it is a robot arm assembling parts in space or an onboard system monitoring the space station, has to react to changes which cannot be foreseen. As a result, apart from having domain-specific knowledge as in current expert systems, a space based AI system should also have general principles of change. This paper presents a modal logic which can not only represent change but also reason with it. Three primitive operations, expansion, contraction and revision are introduced and axioms which specify how the knowledge base should change when the external world changes are also specified. Accordingly the notion of dynamic reasoning is introduced, which unlike the existing forms of reasoning, provide general principles of change. Dynamic reasoning is based on two main principles, namely minimize change and maximize coherence. A possible-world semantics which incorporates the above two principles is also discussed. The paper concludes by discussing how the dynamic reasoning system can be used to specify actions and hence form an integral part of an autonomous reasoning and planning system.

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs

PubMed Central

Tsopra, R.; Venot, A.; Duclos, C.

2014-01-01

Background Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. Methods We investigated two methods (“exclusion” versus “scoring”) for reproducing this reasoning based on antibiotic properties. Results The “exclusion” method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. Discussion This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs. PMID:25954422

Exercise countermeasure protocol management expert system.

PubMed

Webster, L; Chen, J G; Flores, L; Tan, S

1993-04-01

Exercise will be used primarily to countermeasure against deconditioning on extended space flight. In this paper we describe the development and evaluation of an expert system for exercise countermeasure protocol management. Currently, the system includes two major subsystems: baseline prescription and prescription adjustment. The baseline prescription subsystem is designed to provide initial exercise prescriptions while prescription adjustment subsystem is designed to modify the initial prescription based on the exercised progress. The system runs under three different environments: PC, SUN workstation, and Symbolic machine. The inference engine, baseline prescription module, prescription adjustment module and explanation module are developed under the Symbolic environment by using the ART (Automated Reasoning Tool) software. The Sun environment handles database management features and interfaces with PC environment to obtain physical and physiological data from exercise units on-board during the flight. Eight subjects' data have been used to evaluate the system performance by comparing the prescription of nine experienced exercise physiologists and the one prescribed by the expert system. The results of the validation test indicated that the performance of the expert system was acceptable.

Exercise countermeasure protocol management expert system

NASA Technical Reports Server (NTRS)

Webster, L.; Chen, J. G.; Flores, L.; Tan, S.

1993-01-01

Exercise will be used primarily to countermeasure against deconditioning on extended space flight. In this paper we describe the development and evaluation of an expert system for exercise countermeasure protocol management. Currently, the system includes two major subsystems: baseline prescription and prescription adjustment. The baseline prescription subsystem is designed to provide initial exercise prescriptions while prescription adjustment subsystem is designed to modify the initial prescription based on the exercised progress. The system runs under three different environments: PC, SUN workstation, and Symbolic machine. The inference engine, baseline prescription module, prescription adjustment module and explanation module are developed under the Symbolic environment by using the ART (Automated Reasoning Tool) software. The Sun environment handles database management features and interfaces with PC environment to obtain physical and physiological data from exercise units on-board during the flight. Eight subjects' data have been used to evaluate the system performance by comparing the prescription of nine experienced exercise physiologists and the one prescribed by the expert system. The results of the validation test indicated that the performance of the expert system was acceptable.

Two implementations of the Expert System for the Flight Analysis System (ESFAS) project

NASA Technical Reports Server (NTRS)

Wang, Lui

1988-01-01

A comparison is made between the two most sophisticated expert system building tools, the Automated Reasoning Tool (ART) and the Knowledge Engineering Environment (KEE). The same problem domain (ESFAS) was used in making the comparison. The Expert System for the Flight Analysis System (ESFAS) acts as an intelligent front end for the Flight Analysis System (FAS). FAS is a complex configuration controlled set of interrelated processors (FORTRAN routines) which will be used by the Mission Planning and Analysis Div. (MPAD) to design and analyze Shuttle and potential Space Station missions. Implementations of ESFAS are described. The two versions represent very different programming paradigms; ART uses rules and KEE uses objects. Due to each of the tools philosophical differences, KEE is implemented using a depth first traversal algorithm, whereas ART uses a user directed traversal method. Either tool could be used to solve this particular problem.

A new hybrid case-based reasoning approach for medical diagnosis systems.

PubMed

Sharaf-El-Deen, Dina A; Moawad, Ibrahim F; Khalifa, M E

2014-02-01

Case-Based Reasoning (CBR) has been applied in many different medical applications. Due to the complexities and the diversities of this domain, most medical CBR systems become hybrid. Besides, the case adaptation process in CBR is often a challenging issue as it is traditionally carried out manually by domain experts. In this paper, a new hybrid case-based reasoning approach for medical diagnosis systems is proposed to improve the accuracy of the retrieval-only CBR systems. The approach integrates case-based reasoning and rule-based reasoning, and also applies the adaptation process automatically by exploiting adaptation rules. Both adaptation rules and reasoning rules are generated from the case-base. After solving a new case, the case-base is expanded, and both adaptation and reasoning rules are updated. To evaluate the proposed approach, a prototype was implemented and experimented to diagnose breast cancer and thyroid diseases. The final results show that the proposed approach increases the diagnosing accuracy of the retrieval-only CBR systems, and provides a reliable accuracy comparing to the current breast cancer and thyroid diagnosis systems.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

PubMed

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

PubMed Central

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

A knowledge-based expert system for scheduling of airborne astronomical observations

NASA Technical Reports Server (NTRS)

Nachtsheim, P. R.; Gevarter, W. B.; Stutz, J. C.; Banda, C. P.

1985-01-01

The Kuiper Airborne Observatory Scheduler (KAOS) is a knowledge-based expert system developed at NASA Ames Research Center to assist in route planning of a C-141 flying astronomical observatory. This program determines a sequence of flight legs that enables sequential observations of a set of heavenly bodies derived from a list of desirable objects. The possible flight legs are constrained by problems of observability, avoiding flyovers of warning and restricted military zones, and running out of fuel. A significant contribution of the KAOS program is that it couples computational capability with a reasoning system.

An operation support expert system based on on-line dynamics simulation and fuzzy reasoning for startup schedule optimization in fossil power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsumoto, H.; Eki, Y.; Kaji, A.

1993-12-01

An expert system which can support operators of fossil power plants in creating the optimum startup schedule and executing it accurately is described. The optimum turbine speed-up and load-up pattern is obtained through an iterative manner which is based on fuzzy resonating using quantitative calculations as plant dynamics models and qualitative knowledge as schedule optimization rules with fuzziness. The rules represent relationships between stress margins and modification rates of the schedule parameters. Simulations analysis proves that the system provides quick and accurate plant startups.

Human Benchmarking of Expert Systems. Literature Review

DTIC Science & Technology

1990-01-01

effetiveness of the development procedures used in order to predict whether the aplication of similar approaches will likely have effective and...they used in their learning and problem solving. We will describe these approaches later. Reasoning. Reasoning usually includes inference. Because to ... in the software engineering process. For example, existing approaches to software evaluation in the military are based on a model of conventional

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

Perspectives on knowledge in engineering design

NASA Technical Reports Server (NTRS)

Rasdorf, W. J.

1985-01-01

Various perspectives are given of the knowledge currently used in engineering design, specifically dealing with knowledge-based expert systems (KBES). Constructing an expert system often reveals inconsistencies in domain knowledge while formalizing it. The types of domain knowledge (facts, procedures, judgments, and control) differ from the classes of that knowledge (creative, innovative, and routine). The feasible tasks for expert systems can be determined based on these types and classes of knowledge. Interpretive tasks require reasoning about a task in light of the knowledge available, where generative tasks create potential solutions to be tested against constraints. Only after classifying the domain by type and level can the engineer select a knowledge-engineering tool for the domain being considered. The critical features to be weighed after classification are knowledge representation techniques, control strategies, interface requirements, compatibility with traditional systems, and economic considerations.

The Expert Project Management System (EPMS)

NASA Technical Reports Server (NTRS)

Silverman, Barry G.; Diakite, Coty

1986-01-01

Successful project managers (PMs) have been shown to rely on 'intuition,' experience, and analogical reasoning heuristics. For new PMs to be trained and experienced PMs to avoid repeating others' mistakes, it is necessary to make the knowledge and heuristics of successful PMs more widely available. The preparers have evolved a model of PM thought processes over the last decade that is now ready to be implemented as a generic PM aid. This aid consists of a series of 'specialist' expert systems (CRITIC, LIBRARIAN, IDEA MAN, CRAFTSMAN, and WRITER) that communicate with each other via a 'blackboard' architecture. The various specialist expert systems are driven to support PM training and problem solving since any 'answers' they pass to the blackboard are subjected to conflict identification (AGENDA FORMULATOR) and GOAL SETTER inference engines.

The Pacor 2 expert system: A case-based reasoning approach to troubleshooting

NASA Technical Reports Server (NTRS)

Sary, Charisse

1994-01-01

The Packet Processor 2 (Pacor 2) Data Capture Facility (DCF) acquires, captures, and performs level-zero processing of packet telemetry for spaceflight missions that adhere to communication services recommendations established by the Consultative Committee for Space Data Systems (CCSDS). A major goal of this project is to reduce life-cycle costs. One way to achieve this goal is to increase automation. Through automation, using expert systems, and other technologies, staffing requirements will remain static, which will enable the same number of analysts to support more missions. Analysts provide packet telemetry data evaluation and analysis services for all data received. Data that passes this evaluation is forwarded to the Data Distribution Facility (DDF) and released to scientists. Through troubleshooting, data that fails this evaluation is dumped and analyzed to determine if its quality can be improved before it is released. This paper describes a proof-of-concept prototype that troubleshoots data quality problems. The Pacor 2 expert system prototype uses the case-based reasoning (CBR) approach to development, an alternative to a rule-based approach. Because Pacor 2 is not operational, the prototype has been developed using cases that describe existing troubleshooting experience from currently operating missions. Through CBR, this experience will be available to analysts when Pacor 2 becomes operational. As Pacor 2 unique experience is gained, analysts will update the case base. In essence, analysts are training the system as they learn. Once the system has learned the cases most likely to recur, it can serve as an aide to inexperienced analysts, a refresher to experienced analysts for infrequently occurring problems, or a training tool for new analysts. The Expert System Development Methodology (ESDM) is being used to guide development.

Development of a fuzzy logic expert system for pile selection. Master's thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ulshafer, M.L.

1989-01-01

This thesis documents the development of prototype expert system for pile selection for use on microcomputers. It concerns the initial selection of a pile foundation taking into account the parameters such as soil condition, pile length, loading scenario, material availability, contractor experience, and noise or vibration constraints. The prototype expert system called Pile Selection, version 1 (PS1) was developed using an expert system shell FLOPS. FLOPS is a shell based on the AI language OPS5 with many unique features. The system PS1 utilizes all of these unique features. Among the features used are approximate reasoning with fuzzy set theory, themore » blackboard architecture, and the emulated parallel processing of fuzzy production rules. A comprehensive review of the parameters used in selecting a pile was made, and the effects of the uncertainties associated with the vagueness of these parameters was examined in detail. Fuzzy set theory was utilized to deal with such uncertainties and provides the basis for developing a method for determining the best possible choice of piles for a given situation. Details of the development of PS1, including documenting and collating pile information for use in the expert knowledge data bases, are discussed.« less

Raising the AIQ of the Space Station

NASA Technical Reports Server (NTRS)

Lum, Henry; Heer, Ewald

1987-01-01

Expert systems and robotics technologies are to be significantly advanced during the Space Station program. Artificial intelligence systems (AI) on the Station will include 'scars', which will permit upgrading the AI capabilities as the Station evolves to autonomy. NASA-Ames is managing the development of the AI systems through a series of demonstrations, the first, controlling a single subsystem, to be performed in 1988. The capabilities being integrated into the first demonstration are described; however, machine learning and goal-driven natural language understanding will not reach a prototype stage until the mid-1990s. Steps which will be taken to endow the computer systems with the ability to move from heuristic reasoning to factual knowledge, i.e., learning from experience, are explored. It is noted that the development of Space Station expert systems depends on the development of experts in Station operations, which will not happen until the Station has been used extensively by crew members.

Integrated Knowledge Based Expert System for Disease Diagnosis System

NASA Astrophysics Data System (ADS)

Arbaiy, Nureize; Sulaiman, Shafiza Eliza; Hassan, Norlida; Afizah Afip, Zehan

2017-08-01

The role and importance of healthcare systems to improve quality of life and social welfare in a society have been well recognized. Attention should be given to raise awareness and implementing appropriate measures to improve health care. Therefore, a computer based system is developed to serve as an alternative for people to self-diagnose their health status based on given symptoms. This strategy should be emphasized so that people can utilize the information correctly as a reference to enjoy healthier life. Hence, a Web-based Community Center for Healthcare Diagnosis system is developed based on expert system technique. Expert system reasoning technique is employed in the system to enable information about treatment and prevention of the diseases based on given symptoms. At present, three diseases are included which are arthritis, thalassemia and pneumococcal. Sets of rule and fact are managed in the knowledge based system. Web based technology is used as a platform to disseminate the information to users in order for them to optimize the information appropriately. This system will benefit people who wish to increase health awareness and seek expert knowledge on the diseases by performing self-diagnosis for early disease detection.

Computer assisted diagnosis in renal nuclear medicine: rationale, methodology and interpretative criteria for diuretic renography

PubMed Central

Taylor, Andrew T; Garcia, Ernest V

2014-01-01

The goal of artificial intelligence, expert systems, decision support systems and computer assisted diagnosis (CAD) in imaging is the development and implementation of software to assist in the detection and evaluation of abnormalities, to alert physicians to cognitive biases, to reduce intra and inter-observer variability and to facilitate the interpretation of studies at a faster rate and with a higher level of accuracy. These developments are needed to meet the challenges resulting from a rapid increase in the volume of diagnostic imaging studies coupled with a concurrent increase in the number and complexity of images in each patient data. The convergence of an expanding knowledge base and escalating time constraints increases the likelihood of physician errors. Errors are even more likely when physicians interpret low volume studies such as 99mTc-MAG3 diuretic scans where imagers may have had limited training or experience. Decision support systems include neural networks, case-based reasoning, expert systems and statistical systems. iRENEX (renal expert) is an expert system for diuretic renography that uses a set of rules obtained from human experts to analyze a knowledge base of both clinical parameters and quantitative parameters derived from the renogram. Initial studies have shown that the interpretations provided by iRENEX are comparable to the interpretations of a panel of experts. iRENEX provides immediate patient specific feedback at the time of scan interpretation, can be queried to provide the reasons for its conclusions and can be used as an educational tool to teach trainees to better interpret renal scans. iRENEX also has the capacity to populate a structured reporting module and generate a clear and concise impression based on the elements contained in the report; adherence to the procedural and data entry components of the structured reporting module assures and documents procedural competency. Finally, although the focus is CAD applied to diuretic renography, this review offers a window into the rationale, methodology and broader applications of computer assisted diagnosis in medical imaging. PMID:24484751

Computer Based Intelligence Support: An Integrated Expert System and Decision Support Systems Approach

DTIC Science & Technology

1988-06-01

and for that reason has received considerable attention recently. Of particular interest in this research Is the work of Toulmin et. al. [19793 In...whenever we make a claim there must be some grounds in which to base our conclusion, Toulmin states that our thoughts are generally directed from the...WARRANT will be the absolute reason to believe the CLAIM on the basis of the GROUNDS. For that, Toulmin allows for further BACKING which, in his

Why don't patients enroll in hospice? Can we do anything about it?

PubMed

Vig, Elizabeth K; Starks, Helene; Taylor, Janelle S; Hopley, Elizabeth K; Fryer-Edwards, Kelly

2010-10-01

United States hospice organizations aim to provide quality, patient-centered end-of-life care to patients in the last 6 months of life, yet some of these organizations observe that some hospice-eligible patients who are referred to hospice do not initially enroll. To identify reasons that eligible patients do not enroll in hospice (phase 1). To identify strategies used by hospice providers to address these reasons (phase 2). Semi-structured interviews analyzed using content analysis. In phase 1, we interviewed 30 patients and/or family members of patients who had a hospice admissions visit, but who did not enroll. In phase 2, we interviewed 19 hospice staff and national experts. In phase 1, we asked participants to describe the patient's illness, the hospice referral, and why they had not enrolled. We performed a content analysis to characterize their reasons for not enrolling in hospice. In phase 2, we enrolled hospice admissions staff and hospice experts. We asked them to describe how they would respond to each reason (from phase 1) during an admissions visit with a potential new hospice patient. We identified key phrases, and summarized their recommendations. Reasons that patients hadn't enrolled fell into three broad categories: patient/family perceptions (e.g., "not ready"), hospice specific issues (e.g., variable definitions of hospice-eligible patients), and systems issues (e.g., concerns about continuity of care). Hospice staff/experts had encountered each reason, and offered strategies at the individual and organizational level for responding. In hopes of increasing hospice enrollment among hospice-eligible patients, non-hospice and hospice clinicians may want to adopt some of the strategies used by hospice staff/experts for talking about hospice with patients/families and may want to familiarize themselves with the differences between hospice organizations in their area. Hospices may want to reconsider their admission policies and procedures in light of patients' and families' perceptions and concerns.

Categorization and reasoning among tree experts: do all roads lead to Rome?

PubMed

Medin, D L; Lynch, E B; Coley, J D; Atran, S

1997-02-01

To what degree do conceptual systems reflect universal patterns of featural covariation in the world (similarity) or universal organizing principles of mind, and to what degree do they reflect specific goals, theories, and beliefs of the categorizer? This question was addressed in experiments concerned with categorization and reasoning among different types of tree experts (e.g., taxonomists, landscape workers, parks maintenance personnel). The results show an intriguing pattern of similarities and differences. Differences in sorting between taxonomists and maintenance workers reflect differences in weighting of morphological features. Landscape workers, in contrast, sort trees into goal-derived categories based on utilitarian concerns. These sorting patterns carry over into category-based reasoning for the taxonomists and maintenance personnel but not the landscape workers. These generalizations interact with taxonomic rank and suggest that the genus (or folk generic) level is relatively and in some cases absolutely privileged. Implications of these findings for theories of categorization are discussed.

Knowledge From Pictures (KFP)

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Paterra, Frank; Bailin, Sidney

1993-01-01

The old maxim goes: 'A picture is worth a thousand words'. The objective of the research reported in this paper is to demonstrate this idea as it relates to the knowledge acquisition process and the automated development of an expert system's rule base. A prototype tool, the Knowledge From Pictures (KFP) tool, has been developed which configures an expert system's rule base by an automated analysis of and reasoning about a 'picture', i.e., a graphical representation of some target system to be supported by the diagnostic capabilities of the expert system under development. This rule base, when refined, could then be used by the expert system for target system monitoring and fault analysis in an operational setting. Most people, when faced with the problem of understanding the behavior of a complicated system, resort to the use of some picture or graphical representation of the system as an aid in thinking about it. This depiction provides a means of helping the individual to visualize the bahavior and dynamics of the system under study. An analysis of the picture augmented with the individual's background information, allows the problem solver to codify knowledge about the system. This knowledge can, in turn, be used to develop computer programs to automatically monitor the system's performance. The approach taken is this research was to mimic this knowledge acquisition paradigm. A prototype tool was developed which provides the user: (1) a mechanism for graphically representing sample system-configurations appropriate for the domain, and (2) a linguistic device for annotating the graphical representation with the behaviors and mutual influences of the components depicted in the graphic. The KFP tool, reasoning from the graphical depiction along with user-supplied annotations of component behaviors and inter-component influences, generates a rule base that could be used in automating the fault detection, isolation, and repair of the system.

Artificial intelligence within the chemical laboratory.

PubMed

Winkel, P

1994-01-01

Various techniques within the area of artificial intelligence such as expert systems and neural networks may play a role during the problem-solving processes within the clinical biochemical laboratory. Neural network analysis provides a non-algorithmic approach to information processing, which results in the ability of the computer to form associations and to recognize patterns or classes among data. It belongs to the machine learning techniques which also include probabilistic techniques such as discriminant function analysis and logistic regression and information theoretical techniques. These techniques may be used to extract knowledge from example patients to optimize decision limits and identify clinically important laboratory quantities. An expert system may be defined as a computer program that can give advice in a well-defined area of expertise and is able to explain its reasoning. Declarative knowledge consists of statements about logical or empirical relationships between things. Expert systems typically separate declarative knowledge residing in a knowledge base from the inference engine: an algorithm that dynamically directs and controls the system when it searches its knowledge base. A tool is an expert system without a knowledge base. The developer of an expert system uses a tool by entering knowledge into the system. Many, if not the majority of problems encountered at the laboratory level are procedural. A problem is procedural if it is possible to write up a step-by-step description of the expert's work or if it can be represented by a decision tree. To solve problems of this type only small expert system tools and/or conventional programming are required.(ABSTRACT TRUNCATED AT 250 WORDS)

Monitoring real-time navigation processes using the automated reasoning tool (ART)

NASA Technical Reports Server (NTRS)

Maletz, M. C.; Culbert, C. J.

1985-01-01

An expert system is described for monitoring and controlling navigation processes in real-time. The ART-based system features data-driven computation, accommodation of synchronous and asynchronous data, temporal modeling for individual time intervals and chains of time intervals, and hypothetical reasoning capabilities that consider alternative interpretations of the state of navigation processes. The concept is illustrated in terms of the NAVEX system for monitoring and controlling the high speed ground navigation console for Mission Control at Johnson Space Center. The reasoning processes are outlined, including techniques used to consider alternative data interpretations. Installation of the system has permitted using a single operator, instead of three, to monitor the ascent and entry phases of a Shuttle mission.

Integrating Human and Computer Intelligence. Technical Report No. 32.

ERIC Educational Resources Information Center

Pea, Roy D.

This paper explores the thesis that advances in computer applications and artificial intelligence have important implications for the study of development and learning in psychology. Current approaches to the use of computers as devices for problem solving, reasoning, and thinking--i.e., expert systems and intelligent tutoring systems--are…

Substitution of Assisted Living Services by Assistive Technology - Experts Opinions and Technical Feasibility.

PubMed

Schwartze, Jonas; Prekazi, Arianit; Schrom, Harald; Marschollek, Michael

2017-01-01

Ambient assisted living (AAL) may support ageing in place but is primarily driven by technology. The aim of this work is, to identifying reasons to move into assisted living institutions, their range of service and possible substitutability. We did semi-structured interviews with five experts from assisted living institutions and used results to design and implement assistive technologies in an AAL environment using BASIS, a cross domain bus system for smart buildings. Reasons for moving to assisted living institutions are expected benefits for chronic health problems, safety, social isolation and carefree living. We implemented six application systems for inactivity monitoring, stove shutdown, air quality monitoring, medication and appointment reminders, detection of unwanted situations before leaving and optical ringing of the doorbell. Substitution of selected assisted living services is feasible and has potential to delay necessity to move into assisted living institution if complement social services are installed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friedman-Hill, Ernest

Java Expert Shell System - Jess - is a rule engine and scripting environment written entirely in Sun's Java language, Jess was orginially inspired by the CLIPS expert system shell, but has grown int a complete, distinct JAVA-influenced environment of its own. Using Jess, you can build Java applets and applications that have the capacity to "reason" using knowledge you supply in the form of declarative rules. Jess is surprisingly fast, and for some problems is faster than CLIPS, in that many Jess scripts are valid CLIPS scripts and vice-versa. Like CLIPS, Jess uses the Rete algorithm to process rules,more » a very efficient mechanism for solving the difficult many-to-many matching problem. Jess adds many features to CLIPS, including backwards chaining and the ability to manipulate and directly reason about Java objects. Jess is also a powerful Java scripting environment, from which you can create Java objects and call Java methods without compiling any Java Code.« less

Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing.

PubMed

Brasil, L M; de Azevedo, F M; Barreto, J M

2001-09-01

This paper proposes a hybrid expert system (HES) to minimise some complexity problems pervasive to the artificial intelligence such as: the knowledge elicitation process, known as the bottleneck of expert systems; the model choice for knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to obtain the explanation on how the network arrived to a conclusion. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system. A case study is presented (e.g. epileptic crisis) with the problem definition and simulations. Results are also discussed.

Developing Students' Reasoning about Samples and Sampling Variability as a Path to Expert Statistical Thinking

ERIC Educational Resources Information Center

Garfield, Joan; Le, Laura; Zieffler, Andrew; Ben-Zvi, Dani

2015-01-01

This paper describes the importance of developing students' reasoning about samples and sampling variability as a foundation for statistical thinking. Research on expert-novice thinking as well as statistical thinking is reviewed and compared. A case is made that statistical thinking is a type of expert thinking, and as such, research…

How Expert Clinicians Intuitively Recognize a Medical Diagnosis.

PubMed

Brush, John E; Sherbino, Jonathan; Norman, Geoffrey R

2017-06-01

Research has shown that expert clinicians make a medical diagnosis through a process of hypothesis generation and verification. Experts begin the diagnostic process by generating a list of diagnostic hypotheses using intuitive, nonanalytic reasoning. Analytic reasoning then allows the clinician to test and verify or reject each hypothesis, leading to a diagnostic conclusion. In this article, we focus on the initial step of hypothesis generation and review how expert clinicians use experiential knowledge to intuitively recognize a medical diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Relative Expertise in an Everyday Reasoning Task: Epistemic Understanding, Problem Representation, and Reasoning Competence

ERIC Educational Resources Information Center

Weinstock, Michael

2009-01-01

Experts in cognitive domains differ from non-experts in how they represent problems and knowledge, and in their epistemic understandings of tasks in their domain of expertise. This study investigates whether task-specific epistemic understanding also underlies the representation of knowledge on an everyday reasoning task on which the competent…

Hybrid Architectures and Their Impact on Intelligent Design

NASA Technical Reports Server (NTRS)

Kandel, Abe

1996-01-01

In this presentation we investigate a novel framework for the design of autonomous fuzzy intelligent systems. The system integrates the following modules into a single autonomous entity: (1) a fuzzy expert system; (2) artificial neural network; (3) genetic algorithm; and (4) case-base reasoning. We describe the integration of these units into one intelligent structure and discuss potential applications.

System control module diagnostic Expert Assistant

NASA Technical Reports Server (NTRS)

Flores, Luis M.; Hansen, Roger F.

1990-01-01

The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

Problem-solving strategies in psychiatry: differences between experts and novices in diagnostic accuracy and reasoning.

PubMed

Gabriel, Adel; Violato, Claudio

2013-01-01

The purpose of this study was to examine and compare diagnostic success and its relationship with the diagnostic reasoning process between novices and experts in psychiatry. Nine volunteers, comprising five expert psychiatrists and four clinical clerks, completed a think-aloud protocol while attempting to make a DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) diagnosis of a selected case with both Axis I and Axis III diagnoses. Expert psychiatrists made significantly more successful diagnoses for both the primary psychiatric and medical diagnoses than clinical clerks. Expert psychiatrists also gave fewer differential options. Analyzing the think-aloud protocols, expert psychiatrists were much more organized, made fewer mistakes, and utilized significantly less time to access their knowledge than clinical clerks. Both novices and experts seemed to use the hypothetic-deductive and scheme-inductive approaches to diagnosis. However, experts utilized hypothetic-deductive approaches significantly more often than novices. The hypothetic-deductive diagnostic strategy was utilized more than the scheme-inductive approach by both expert psychiatrists and clinical clerks. However, a specific relationship between diagnostic reasoning and diagnostic success could not be identified in this small pilot study. The author recommends a larger study that would include a detailed analysis of the think-aloud protocols.

Using computer aided case based reasoning to support clinical reasoning in community occupational therapy.

PubMed

Taylor, Bruce; Robertson, David; Wiratunga, Nirmalie; Craw, Susan; Mitchell, Dawn; Stewart, Elaine

2007-08-01

Community occupational therapists have long been involved in the provision of environmental control systems. Diverse electronic technologies with the potential to improve the health and quality of life of selected clients have developed rapidly in recent years. Occupational therapists employ clinical reasoning in order to determine the most appropriate technology to meet the needs of individual clients. This paper describes a number of the drivers that may increase the adoption of information and communication technologies in the occupational therapy profession. It outlines case based reasoning as understood in the domains of expert systems and knowledge management and presents the preliminary results of an ongoing investigation into the potential of a prototype computer aided case based reasoning tool to support the clinical reasoning of community occupational therapists in the process of assisting clients to choose home electronic assistive or smart house technology.

TEXSYS. [a knowledge based system for the Space Station Freedom thermal control system test-bed

NASA Technical Reports Server (NTRS)

Bull, John

1990-01-01

The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.

Engine Data Interpretation System (EDIS), phase 2

NASA Technical Reports Server (NTRS)

Cost, Thomas L.; Hofmann, Martin O.

1991-01-01

A prototype of an expert system was developed which applies qualitative constraint-based reasoning to the task of post-test analysis of data resulting from a rocket engine firing. Data anomalies are detected and corresponding faults are diagnosed. Engine behavior is reconstructed using measured data and knowledge about engine behavior. Knowledge about common faults guides but does not restrict the search for the best explanation in terms of hypothesized faults. The system contains domain knowledge about the behavior of common rocket engine components and was configured for use with the Space Shuttle Main Engine (SSME). A graphical user interface allows an expert user to intimately interact with the system during diagnosis. The system was applied to data taken during actual SSME tests where data anomalies were observed.

Diagnostic reasoning strategies and diagnostic success.

PubMed

Coderre, S; Mandin, H; Harasym, P H; Fick, G H

2003-08-01

Cognitive psychology research supports the notion that experts use mental frameworks or "schemes", both to organize knowledge in memory and to solve clinical problems. The central purpose of this study was to determine the relationship between problem-solving strategies and the likelihood of diagnostic success. Think-aloud protocols were collected to determine the diagnostic reasoning used by experts and non-experts when attempting to diagnose clinical presentations in gastroenterology. Using logistic regression analysis, the study found that there is a relationship between diagnostic reasoning strategy and the likelihood of diagnostic success. Compared to hypothetico-deductive reasoning, the odds of diagnostic success were significantly greater when subjects used the diagnostic strategies of pattern recognition and scheme-inductive reasoning. Two other factors emerged as independent determinants of diagnostic success: expertise and clinical presentation. Not surprisingly, experts outperformed novices, while the content area of the clinical cases in each of the four clinical presentations demonstrated varying degrees of difficulty and thus diagnostic success. These findings have significant implications for medical educators. It supports the introduction of "schemes" as a means of enhancing memory organization and improving diagnostic success.

Uncertainty reasoning in expert systems

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik

1993-01-01

Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible' into an actual control. To apply this transformation, one must choose appropriate methods for reasoning with uncertainty, i.e., one must: (1) choose the representation for words like 'small', 'big'; (2) choose operations corresponding to 'and' and 'or'; (3) choose a method that transforms the resulting uncertain control recommendations into a precise control strategy. The wrong choice can drastically affect the quality of the resulting control, so the problem of choosing the right procedure is very important. From a mathematical viewpoint these choice problems correspond to non-linear optimization and are therefore extremely difficult. In this project, a new mathematical formalism (based on group theory) is developed that allows us to solve the problem of optimal choice and thus: (1) explain why the existing choices are really the best (in some situations); (2) explain a rather mysterious fact that fuzzy control (i.e., control based on the experts' knowledge) is often better than the control by these same experts; and (3) give choice recommendations for the cases when traditional choices do not work.

Creating an ontology driven rules base for an expert system for medical diagnosis.

PubMed

Bertaud Gounot, Valérie; Donfack, Valéry; Lasbleiz, Jérémy; Bourde, Annabel; Duvauferrier, Régis

2011-01-01

Expert systems of the 1980s have failed on the difficulties of maintaining large rule bases. The current work proposes a method to achieve and maintain rule bases grounded on ontologies (like NCIT). The process described here for an expert system on plasma cell disorder encompasses extraction of a sub-ontology and automatic and comprehensive generation of production rules. The creation of rules is not based directly on classes, but on individuals (instances). Instances can be considered as prototypes of diseases formally defined by "destrictions" in the ontology. Thus, it is possible to use this process to make diagnoses of diseases. The perspectives of this work are considered: the process described with an ontology formalized in OWL1 can be extended by using an ontology in OWL2 and allow reasoning about numerical data in addition to symbolic data.

Expert diagnostics system as a part of analysis software for power mission operations

NASA Technical Reports Server (NTRS)

Harris, Jennifer A.; Bahrami, Khosrow A.

1993-01-01

The operation of interplanetary spacecraft at JPL has become an increasingly complex activity. This complexity is due to advanced spacecraft designs and ambitious mission objectives which lead to operations requirements that are more demanding than those of any previous mission. For this reason, several productivity enhancement measures are underway at JPL within mission operations, particularly in the spacecraft analysis area. These measures aimed at spacecraft analysis include: the development of a multi-mission, multi-subsystem operations environment; the introduction of automated tools into this environment; and the development of an expert diagnostics system. This paper discusses an effort to integrate the above mentioned productivity enhancement measures. A prototype was developed that integrates an expert diagnostics system into a multi-mission, multi-subsystem operations environment using the Galileo Power / Pyro Subsystem as a testbed. This prototype will be discussed in addition to background information associated with it.

Design of Composite Structures Using Knowledge-Based and Case Based Reasoning

NASA Technical Reports Server (NTRS)

Lambright, Jonathan Paul

1996-01-01

A method of using knowledge based and case based reasoning to assist designers during conceptual design tasks of composite structures was proposed. The cooperative use of heuristics, procedural knowledge, and previous similar design cases suggests a potential reduction in design cycle time and ultimately product lead time. The hypothesis of this work is that the design process of composite structures can be improved by using Case-Based Reasoning (CBR) and Knowledge-Based (KB) reasoning in the early design stages. The technique of using knowledge-based and case-based reasoning facilitates the gathering of disparate information into one location that is easily and readily available. The method suggests that the inclusion of downstream life-cycle issues into the conceptual design phase reduces potential of defective, and sub-optimal composite structures. Three industry experts were interviewed extensively. The experts provided design rules, previous design cases, and test problems. A Knowledge Based Reasoning system was developed using the CLIPS (C Language Interpretive Procedural System) environment and a Case Based Reasoning System was developed using the Design Memory Utility For Sharing Experiences (MUSE) xviii environment. A Design Characteristic State (DCS) was used to document the design specifications, constraints, and problem areas using attribute-value pair relationships. The DCS provided consistent design information between the knowledge base and case base. Results indicated that the use of knowledge based and case based reasoning provided a robust design environment for composite structures. The knowledge base provided design guidance from well defined rules and procedural knowledge. The case base provided suggestions on design and manufacturing techniques based on previous similar designs and warnings of potential problems and pitfalls. The case base complemented the knowledge base and extended the problem solving capability beyond the existence of limited well defined rules. The findings indicated that the technique is most effective when used as a design aid and not as a tool to totally automate the composites design process. Other areas of application and implications for future research are discussed.

MOM: A meteorological data checking expert system in CLIPS

NASA Technical Reports Server (NTRS)

Odonnell, Richard

1990-01-01

Meteorologists have long faced the problem of verifying the data they use. Experience shows that there is a sizable number of errors in the data reported by meteorological observers. This is unacceptable for computer forecast models, which depend on accurate data for accurate results. Most errors that occur in meteorological data are obvious to the meteorologist, but time constraints prevent hand-checking. For this reason, it is necessary to have a 'front end' to the computer model to ensure the accuracy of input. Various approaches to automatic data quality control have been developed by several groups. MOM is a rule-based system implemented in CLIPS and utilizing 'consistency checks' and 'range checks'. The system is generic in the sense that it knows some meteorological principles, regardless of specific station characteristics. Specific constraints kept as CLIPS facts in a separate file provide for system flexibility. Preliminary results show that the expert system has detected some inconsistencies not noticed by a local expert.

SeTES, a Self-Teaching Expert System for the analysis, design and prediction of gas production from shales and a prototype for a new generation of Expert Systems in the Earth Sciences

NASA Astrophysics Data System (ADS)

Kuzma, H. A.; Boyle, K.; Pullman, S.; Reagan, M. T.; Moridis, G. J.; Blasingame, T. A.; Rector, J. W.; Nikolaou, M.

2010-12-01

A Self Teaching Expert System (SeTES) is being developed for the analysis, design and prediction of gas production from shales. An Expert System is a computer program designed to answer questions or clarify uncertainties that its designers did not necessarily envision which would otherwise have to be addressed by consultation with one or more human experts. Modern developments in computer learning, data mining, database management, web integration and cheap computing power are bringing the promise of expert systems to fruition. SeTES is a partial successor to Prospector, a system to aid in the identification and evaluation of mineral deposits developed by Stanford University and the USGS in the late 1970s, and one of the most famous early expert systems. Instead of the text dialogue used in early systems, the web user interface of SeTES helps a non-expert user to articulate, clarify and reason about a problem by navigating through a series of interactive wizards. The wizards identify potential solutions to queries by retrieving and combining together relevant records from a database. Inferences, decisions and predictions are made from incomplete and noisy inputs using a series of probabilistic models (Bayesian Networks) which incorporate records from the database, physical laws and empirical knowledge in the form of prior probability distributions. The database is mainly populated with empirical measurements, however an automatic algorithm supplements sparse data with synthetic data obtained through physical modeling. This constitutes the mechanism for how SeTES self-teaches. SeTES’ predictive power is expected to grow as users contribute more data into the system. Samples are appropriately weighted to favor high quality empirical data over low quality or synthetic data. Finally, a set of data visualization tools digests the output measurements into graphical outputs.

Experienced and less-experienced nurses' diagnostic reasoning: implications for fostering students' critical thinking.

PubMed

Ferrario, Catherine G

2003-01-01

To compare the use of mental representations (heuristics) in diagnostic reasoning of expert (> or = 5 years' experience) and novice (< 5 years' experience) emergency nurses. Clinical simulations were completed by a nationwide randomly selected sample of 173 experienced and 46 less-experienced emergency nurses (N = 219). Experienced nurses used the heuristic, Judging by Causal Systems (diagnostic inferences deduced from systems of causal factors) significantly more did than less-experienced nurses. Standardized nursing diagnoses may cut short the time needed to develop representational thinking and spare cognitive reserves for reasoning needed for complex patients. Faculty need to promote student's cognitive development through strategies that promote active, reflective, and integrative learning.

Intelligent Chatter Bot for Regulation Search

NASA Astrophysics Data System (ADS)

De Luise, María Daniela López; Pascal, Andrés; Saad, Ben; Álvarez, Claudia; Pescio, Pablo; Carrilero, Patricio; Malgor, Rafael; Díaz, Joaquín

2016-01-01

This communication presents a functional prototype, named PTAH, implementing a linguistic model focused on regulations in Spanish. Its global architecture, the reasoning model and short statistics are provided for the prototype. It is mainly a conversational robot linked to an Expert System by a module with many intelligent linguistic filters, implementing the reasoning model of an expert. It is focused on bylaws, regulations, jurisprudence and customized background representing entity mission, vision and profile. This Structure and model are generic enough to self-adapt to any regulatory environment, but as a first step, it was limited to an academic field. This way it is possible to limit the slang and data numbers. The foundations of the linguistic model are also outlined and the way the architecture implements the key features of the behavior.

A knowledge authoring tool for clinical decision support.

PubMed

Dunsmuir, Dustin; Daniels, Jeremy; Brouse, Christopher; Ford, Simon; Ansermino, J Mark

2008-06-01

Anesthesiologists in the operating room are unable to constantly monitor all data generated by physiological monitors. They are further distracted by clinical and educational tasks. An expert system would ideally provide assistance to the anesthesiologist in this data-rich environment. Clinical monitoring expert systems have not been widely adopted, as traditional methods of knowledge encoding require both expert medical and programming skills, making knowledge acquisition difficult. A software application was developed for use as a knowledge authoring tool for physiological monitoring. This application enables clinicians to create knowledge rules without the need of a knowledge engineer or programmer. These rules are designed to provide clinical diagnosis, explanations and treatment advice for optimal patient care to the clinician in real time. By intelligently combining data from physiological monitors and demographical data sources the expert system can use these rules to assist in monitoring the patient. The knowledge authoring process is simplified by limiting connective relationships between rules. The application is designed to allow open collaboration between communities of clinicians to build a library of rules for clinical use. This design provides clinicians with a system for parameter surveillance and expert advice with a transparent pathway of reasoning. A usability evaluation demonstrated that anesthesiologists can rapidly develop useful rules for use in a predefined clinical scenario.

A knowledge creation info-structure to acquire and crystallize the tacit knowledge of health-care experts.

PubMed

Abidi, Syed Sibte Raza; Cheah, Yu-N; Curran, Janet

2005-06-01

Tacit knowledge of health-care experts is an important source of experiential know-how, yet due to various operational and technical reasons, such health-care knowledge is not entirely harnessed and put into professional practice. Emerging knowledge-management (KM) solutions suggest strategies to acquire the seemingly intractable and nonarticulated tacit knowledge of health-care experts. This paper presents a KM methodology, together with its computational implementation, to 1) acquire the tacit knowledge possessed by health-care experts; 2) represent the acquired tacit health-care knowledge in a computational formalism--i.e., clinical scenarios--that allows the reuse of stored knowledge to acquire tacit knowledge; and 3) crystallize the acquired tacit knowledge so that it is validated for health-care decision-support and medical education systems.

A case-based reasoning tool for breast cancer knowledge management with data mining concepts and techniques

NASA Astrophysics Data System (ADS)

Demigha, Souâd.

2016-03-01

The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.

Deep-reasoning fault diagnosis - An aid and a model

NASA Technical Reports Server (NTRS)

Yoon, Wan Chul; Hammer, John M.

1988-01-01

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the human's casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding.

Experiments with microcomputer-based artificial intelligence environments

USGS Publications Warehouse

Summers, E.G.; MacDonald, R.A.

1988-01-01

The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

Multimodal hybrid reasoning methodology for personalized wellbeing services.

PubMed

Ali, Rahman; Afzal, Muhammad; Hussain, Maqbool; Ali, Maqbool; Siddiqi, Muhammad Hameed; Lee, Sungyoung; Ho Kang, Byeong

2016-02-01

A wellness system provides wellbeing recommendations to support experts in promoting a healthier lifestyle and inducing individuals to adopt healthy habits. Adopting physical activity effectively promotes a healthier lifestyle. A physical activity recommendation system assists users to adopt daily routines to form a best practice of life by involving themselves in healthy physical activities. Traditional physical activity recommendation systems focus on general recommendations applicable to a community of users rather than specific individuals. These recommendations are general in nature and are fit for the community at a certain level, but they are not relevant to every individual based on specific requirements and personal interests. To cover this aspect, we propose a multimodal hybrid reasoning methodology (HRM) that generates personalized physical activity recommendations according to the user׳s specific needs and personal interests. The methodology integrates the rule-based reasoning (RBR), case-based reasoning (CBR), and preference-based reasoning (PBR) approaches in a linear combination that enables personalization of recommendations. RBR uses explicit knowledge rules from physical activity guidelines, CBR uses implicit knowledge from experts׳ past experiences, and PBR uses users׳ personal interests and preferences. To validate the methodology, a weight management scenario is considered and experimented with. The RBR part of the methodology generates goal, weight status, and plan recommendations, the CBR part suggests the top three relevant physical activities for executing the recommended plan, and the PBR part filters out irrelevant recommendations from the suggested ones using the user׳s personal preferences and interests. To evaluate the methodology, a baseline-RBR system is developed, which is improved first using ranged rules and ultimately using a hybrid-CBR. A comparison of the results of these systems shows that hybrid-CBR outperforms the modified-RBR and baseline-RBR systems. Hybrid-CBR yields a 0.94% recall, a 0.97% precision, a 0.95% f-score, and low Type I and Type II errors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Case-Based Capture and Reuse of Aerospace Design Rationale

NASA Technical Reports Server (NTRS)

Leake, David B.

1998-01-01

The goal of this project is to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project applies case-based reasoning (CBR) and concept mapping (CMAP) tools to the task of capturing, organizing, and interactively accessing experiences or "cases" encapsulating the methods and rationale underlying expert aerospace design. As stipulated in the award, Indiana University and Ames personnel are collaborating on performance of research and determining the direction of research, to assure that the project focuses on high-value tasks. In the first five months of the project, we have made two visits to Ames Research Center to consult with our NASA collaborators, to learn about the advanced aerospace design tools being developed there, and to identify specific needs for intelligent design support. These meetings identified a number of task areas for applying CBR and concept mapping technology. We jointly selected a first task area to focus on: Acquiring the convergence criteria that experts use to guide the selection of useful data from a set of numerical simulations of high-lift systems. During the first funding period, we developed two software systems. First, we have adapted a CBR system developed at Indiana University into a prototype case-based reasoning shell to capture and retrieve information about design experiences, with the sample task of capturing and reusing experts' intuitive criteria for determining convergence (work conducted at Indiana University). Second, we have also adapted and refined existing concept mapping tools that will be used to clarify and capture the rationale underlying those experiences, to facilitate understanding of the expert's reasoning and guide future reuse of captured information (work conducted at the University of West Florida). The tools we have developed are designed to be the basis for a general framework for facilitating tasks within systems developed by the Advanced Design Technologies Testbed (ADTT) project at ARC. The tenets of our framework are (1) that the systems developed should leverage a designer's knowledge, rather than attempting to replace it; (2) that learning and user feedback must play a central role, so that the system can adapt to how it is used, and (3) that the learning and feedback processes must be as natural and as unobtrusive as possible. In the second funding period we will extend our current work, applying the tools to capturing higher-level design rationale.

Dissociative identity disorder: Medicolegal challenges.

PubMed

Farrell, Helen M

2011-01-01

Persons with dissociative identity disorder (DID) often present in the criminal justice system rather than the mental health system and perplex experts in both professions. DID is a controversial diagnosis with important medicolegal implications. Defendants have claimed that they committed serious crimes, including rape or murder, while they were in a dissociated state. Asserting that their alter personality committed the bad act, defendants have pleaded not guilty by reason of insanity (NGRI). In such instances, forensic experts are asked to assess the defendant for DID and provide testimony in court. Debate continues over whether DID truly exists, whether expert testimony should be allowed into evidence, and whether it should exculpate defendants for their criminal acts. This article reviews historical and theoretical perspectives on DID, presents cases that illustrate the legal implications and controversies of raising an insanity defense based on multiple personalities, and examines the role of forensic experts asked to comment on DID with the goal of assisting clinicians in the medicolegal assessment of DID in relation to crimes.

40 CFR 194.26 - Expert judgment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to elicit judgments from experts, the questions or issues presented for elicitation of expert judgment... expert judgment elicitation comports with the level of knowledge required by the questions or issues...

40 CFR 194.26 - Expert judgment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to elicit judgments from experts, the questions or issues presented for elicitation of expert judgment... expert judgment elicitation comports with the level of knowledge required by the questions or issues...

Min and max are the only continuous ampersand-, V-operations for finite logics

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik

1992-01-01

Experts usually express their degrees of belief in their statements by the words of a natural language (like 'maybe', 'perhaps', etc.). If an expert system contains the degrees of beliefs t(A) and t(B) that correspond to the statements A and B, and a user asks this expert system whether 'A&B' is true, then it is necessary to come up with a reasonable estimate for the degree of belief of A&B. The operation that processes t(A) and t(B) into such an estimate t(A&B) is called an &-operation. Many different &-operations have been proposed. Which of them to choose? This can be (in principle) done by interviewing experts and eliciting a &-operation from them, but such a process is very time-consuming and therefore, not always possible. So, usually, to choose a &-operation, the finite set of actually possible degrees of belief is extended to an infinite set (e.g., to an interval (0,1)), define an operation there, and then restrict this operation to the finite set. Only this original finite set is considered. It is shown that a reasonable assumption that an &-operation is continuous (i.e., that gradual change in t(A) and t(B) must lead to a gradual change in t(A&B)), uniquely determines min as an &-operation. Likewise, max is the only continuous V-operation. These results are in good accordance with the experimental analysis of 'and' and 'or' in human beliefs.

Expert Consensus Survey on Medication Adherence in Psychiatric Patients and Use of a Digital Medicine System.

PubMed

Hatch, Ainslie; Docherty, John P; Carpenter, Daniel; Ross, Ruth; Weiden, Peter J

2017-07-01

There is an unmet need to objectively assess adherence problems that are a common cause of unexplained or unexpected suboptimal outcome. A digital medicine system (DMS) has been developed to address this need in patients with serious mental illness. To conduct a quantitative expert consensus survey to (1) assess relative importance of causes of suboptimal outcomes, (2) examine modalities used to assess adherence, (3) provide guidance on when and how to use the DMS in clinical practice once available, and (4) suggest interventions for specific reasons for nonadherence. A panel of 58 experts in psychiatry completed a 23-question survey (October 13 through December 23, 2013) and rated their responses on a 9-point Likert scale. A χ² test of score distributions was used to determine consensus (P < .05). The panel rated adherence as the most important factor in suboptimal outcomes and yet the least likely to be assessed accurately. All predefined uses of the DMS received high mean first-line ratings (≥ 7.4). The experts recognized the utility of the DMS in managing adherence problems, identified clinical situations appropriate for DMS, and assessed potential benefits and challenges of this technology. Consensus was reached on first-line interventions for 10 of 11 reasons for nonadherence. The results provide a guide to clinicians on the evaluation of suboptimal outcomes, when and how to use the DMS, and the most appropriate interventions to address detected adherence problems. © Copyright 2017 Physicians Postgraduate Press, Inc.

Accident diagnosis system based on real-time decision tree expert system

NASA Astrophysics Data System (ADS)

Nicolau, Andressa dos S.; Augusto, João P. da S. C.; Schirru, Roberto

2017-06-01

Safety is one of the most studied topics when referring to power stations. For that reason, sensors and alarms develop an important role in environmental and human protection. When abnormal event happens, it triggers a chain of alarms that must be, somehow, checked by the control room operators. In this case, diagnosis support system can help operators to accurately identify the possible root-cause of the problem in short time. In this article, we present a computational model of a generic diagnose support system based on artificial intelligence, that was applied on the dataset of two real power stations: Angra1 Nuclear Power Plant and Santo Antônio Hydroelectric Plant. The proposed system processes all the information logged in the sequence of events before a shutdown signal using the expert's knowledge inputted into an expert system indicating the chain of events, from the shutdown signal to its root-cause. The results of both applications showed that the support system is a potential tool to help the control room operators identify abnormal events, as accidents and consequently increase the safety.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

A Starter's Guide to Artificial Intelligence.

ERIC Educational Resources Information Center

McConnell, Barry A.; McConnell, Nancy J.

1988-01-01

Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

Software life cycle methodologies and environments

NASA Technical Reports Server (NTRS)

Fridge, Ernest

1991-01-01

Products of this project will significantly improve the quality and productivity of Space Station Freedom Program software processes by: improving software reliability and safety; and broadening the range of problems that can be solved with computational solutions. Projects brings in Computer Aided Software Engineering (CASE) technology for: Environments such as Engineering Script Language/Parts Composition System (ESL/PCS) application generator, Intelligent User Interface for cost avoidance in setting up operational computer runs, Framework programmable platform for defining process and software development work flow control, Process for bringing CASE technology into an organization's culture, and CLIPS/CLIPS Ada language for developing expert systems; and methodologies such as Method for developing fault tolerant, distributed systems and a method for developing systems for common sense reasoning and for solving expert systems problems when only approximate truths are known.

Expert Systems and Command, Control, and Communication System Acquisition

DTIC Science & Technology

1989-03-01

Systems and Command, Control, and Communicaton System Acquisition 12 Personal Author(s) James E. Minnema 13a Type of Report 13b Time Covered 14 Date...isolated strategic planning, unstructured problems, the author feels that this category should also include problems involving the integration of...distinct operational or management control, and structured or semi-structured problem efforts. The reason for this is that integration of a number of

Supervised interpretation of echocardiograms with a psychological model of expert supervision

NASA Astrophysics Data System (ADS)

Revankar, Shriram V.; Sher, David B.; Shalin, Valerie L.; Ramamurthy, Maya

1993-07-01

We have developed a collaborative scheme that facilitates active human supervision of the binary segmentation of an echocardiogram. The scheme complements the reliability of a human expert with the precision of segmentation algorithms. In the developed system, an expert user compares the computer generated segmentation with the original image in a user friendly graphics environment, and interactively indicates the incorrectly classified regions either by pointing or by circling. The precise boundaries of the indicated regions are computed by studying original image properties at that region, and a human visual attention distribution map obtained from the published psychological and psychophysical research. We use the developed system to extract contours of heart chambers from a sequence of two dimensional echocardiograms. We are currently extending this method to incorporate a richer set of inputs from the human supervisor, to facilitate multi-classification of image regions depending on their functionality. We are integrating into our system the knowledge related constraints that cardiologists use, to improve the capabilities of our existing system. This extension involves developing a psychological model of expert reasoning, functional and relational models of typical views in echocardiograms, and corresponding interface modifications to map the suggested actions to image processing algorithms.

Intelligent fault management for the Space Station active thermal control system

NASA Technical Reports Server (NTRS)

Hill, Tim; Faltisco, Robert M.

1992-01-01

The Thermal Advanced Automation Project (TAAP) approach and architecture is described for automating the Space Station Freedom (SSF) Active Thermal Control System (ATCS). The baseline functionally and advanced automation techniques for Fault Detection, Isolation, and Recovery (FDIR) will be compared and contrasted. Advanced automation techniques such as rule-based systems and model-based reasoning should be utilized to efficiently control, monitor, and diagnose this extremely complex physical system. TAAP is developing advanced FDIR software for use on the SSF thermal control system. The goal of TAAP is to join Knowledge-Based System (KBS) technology, using a combination of rules and model-based reasoning, with conventional monitoring and control software in order to maximize autonomy of the ATCS. TAAP's predecessor was NASA's Thermal Expert System (TEXSYS) project which was the first large real-time expert system to use both extensive rules and model-based reasoning to control and perform FDIR on a large, complex physical system. TEXSYS showed that a method is needed for safely and inexpensively testing all possible faults of the ATCS, particularly those potentially damaging to the hardware, in order to develop a fully capable FDIR system. TAAP therefore includes the development of a high-fidelity simulation of the thermal control system. The simulation provides realistic, dynamic ATCS behavior and fault insertion capability for software testing without hardware related risks or expense. In addition, thermal engineers will gain greater confidence in the KBS FDIR software than was possible prior to this kind of simulation testing. The TAAP KBS will initially be a ground-based extension of the baseline ATCS monitoring and control software and could be migrated on-board as additional computation resources are made available.

Strategic Explanations for a Diagnostic Consultation System. Technical Report #8.

ERIC Educational Resources Information Center

Hasling, Diane Warner; And Others

This paper examines the problem of automatic explanation of reasoning, or the ability of a program to discuss what it is doing in some understandable way, particularly as part of an expert system. An introduction presents a general framework in which to view explanation and reviews some of the research in this area. This is followed by a…

PDA: A coupling of knowledge and memory for case-based reasoning

NASA Technical Reports Server (NTRS)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

Clinical reasoning in unimodal interventions in patients with non-specific neck pain in daily physiotherapy practice, a Delphi study.

PubMed

Maissan, Francois; Pool, Jan; Stutterheim, Eric; Wittink, Harriet; Ostelo, Raymond

2018-06-02

Neck pain is the fourth major cause of disability worldwide but sufficient evidence regarding treatment is not available. This study is a first exploratory attempt to gain insight into and consensus on the clinical reasoning of experts in patients with non-specific neck pain. First, we aimed to inventory expert opinions regarding the indication for physiotherapy when, other than neck pain, no positive signs and symptoms and no positive diagnostic tests are present. Secondly, we aimed to determine which measurement instruments are being used and when they are used to support and objectify the clinical reasoning process. Finally, we wanted to establish consensus among experts regarding the use of unimodal interventions in patients with non-specific neck pain, i.e. their sequential linear clinical reasoning. A Delphi study. A Web-based Delphi study was conducted. Fifteen experts (teachers and researchers) participated. Pain alone was deemed not be an indication for physiotherapy treatment. PROMs are mainly used for evaluative purposes and physical tests for diagnostic and evaluative purposes. Eighteen different variants of sequential linear clinical reasoning were investigated within our Delphi study. Only 6 out of 18 variants of sequential linear clinical reasoning reached more than 50% consensus. Pain alone is not an indication for physiotherapy. Insight has been obtained into which measurement instruments are used and when they are used. Consensus about sequential linear lines of clinical reasoning was poor. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predicting and explaining the movement of mesoscale oceanographic features using CLIPS

NASA Technical Reports Server (NTRS)

Bridges, Susan; Chen, Liang-Chun; Lybanon, Matthew

1994-01-01

The Naval Research Laboratory has developed an oceanographic expert system that describes the evolution of mesoscale features in the Gulf Stream region of the northwest Atlantic Ocean. These features include the Gulf Stream current and the warm and cold core eddies associated with the Gulf Stream. An explanation capability was added to the eddy prediction component of the expert system in order to allow the system to justify the reasoning process it uses to make predictions. The eddy prediction and explanation components of the system have recently been redesigned and translated from OPS83 to C and CLIPS and the new system is called WATE (Where Are Those Eddies). The new design has improved the system's readability, understandability and maintainability and will also allow the system to be incorporated into the Semi-Automated Mesoscale Analysis System which will eventually be embedded into the Navy's Tactical Environmental Support System, Third Generation, TESS(3).

Expert reasoning within an object-oriented framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bohn, S.J.; Pennock, K.A.

1991-10-01

A large number of contaminated waste sites across the United States await site remediation efforts. These sites can be physically complex, composed of multiple, possibly interacting, contaminants distributed throughout one or more media. The Remedial Action Assessment System (RAAS) is being designed and developed to support decisions concerning the selection of remediation alternatives. The goal of this system is to broaden the consideration of remediation alternatives, while reducing the time and cost of making these considerations. The Remedial Action Assessment System was designed and constructed using object-oriented techniques. It is a hybrid system which uses a combination of quantitative andmore » qualitative reasoning to consider and suggest remediation alternatives. the reasoning process that drives this application is centered around an object-oriented organization of remediation technology information. This paper briefly describes the waste remediation problem and then discusses the information structure and organization RAAS utilizes to address it. 4 refs., 4 figs.« less

Integrated Formulation of Beacon-Based Exception Analysis for Multimissions

NASA Technical Reports Server (NTRS)

Mackey, Ryan; James, Mark; Park, Han; Zak, Mickail

2003-01-01

Further work on beacon-based exception analysis for multimissions (BEAM), a method of real-time, automated diagnosis of a complex electromechanical systems, has greatly expanded its capability and suitability of application. This expanded formulation, which fully integrates physical models and symbolic analysis, is described. The new formulation of BEAM expands upon previous advanced techniques for analysis of signal data, utilizing mathematical modeling of the system physics, and expert-system reasoning,

Nickel hydrogen battery expert system

NASA Technical Reports Server (NTRS)

Shiva, Sajjan G.

1991-01-01

The Hubble Telescope Battery Testbed at MSFC uses the Nickel Cadmium (NiCd) Battery Expert System (NICBES-2) which supports the evaluation of performance of Hubble Telescope spacecraft batteries and provides alarm diagnosis and action advice. NICBES-2 provides a reasoning system along with a battery domain knowledge base to achieve this battery health management function. An effort is summarized which was used to modify NICBES-2 to accommodate Nickel Hydrogen (NiH2) battery environment now in MSFC testbed. The NICBES-2 is implemented on a Sun Microsystem and is written in SunOS C and Quintus Prolog. The system now operates in a multitasking environment. NICBES-2 spawns three processes: serial port process (SPP); data handler process (DHP); and the expert system process (ESP) in order to process the telemetry data and provide the status and action advice. NICBES-2 performs orbit data gathering, data evaluation, alarm diagnosis and action advice and status and history display functions. The adaptation of NICBES-2 to work with NiH2 battery environment required modification to all of the three component processes.

Applications of artificial intelligence to digital photogrammetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kretsch, J.L.

1988-01-01

The aim of this research was to explore the application of expert systems to digital photogrammetry, specifically to photogrammetric triangulation, feature extraction, and photogrammetric problem solving. In 1987, prototype expert systems were developed for doing system startup, interior orientation, and relative orientation in the mensuration stage. The system explored means of performing diagnostics during the process. In the area of feature extraction, the relationship of metric uncertainty to symbolic uncertainty was the topic of research. Error propagation through the Dempster-Shafer formalism for representing evidence was performed in order to find the variance in the calculated belief values due to errorsmore » in measurements made together the initial evidence needed to being labeling of observed image features with features in an object model. In photogrammetric problem solving, an expert system is under continuous development which seeks to solve photogrammetric problems using mathematical reasoning. The key to the approach used is the representation of knowledge directly in the form of equations, rather than in the form of if-then rules. Then each variable in the equations is treated as a goal to be solved.« less

Expert Design Advisor

DTIC Science & Technology

1990-10-01

to economic, technological, spatial or logistic concerns, or involve training, man-machine interfaces, or integration into existing systems. Once the...probabilistic reasoning, mixed analysis- and simulation-oriented, mixed computation- and communication-oriented, nonpreemptive static priority...scheduling base, nonrandomized, preemptive static priority scheduling base, randomized, simulation-oriented, and static scheduling base. The selection of both

Elicitation Support Requirements of Multi-Expertise Teams

ERIC Educational Resources Information Center

Bitter-Rijpkema, Marlies; Martens, Rob; Jochems, Wim

2005-01-01

Tools to support knowledge elicitation are used more and more in situations where employees or students collaborate using the computer. Studies indicate that differences exist between experts and novices regarding their methods of work and reasoning. However, the commonly preferred approach tends to deal with team members as a single system with…

The Moral Impotence of Contemporary Experts

ERIC Educational Resources Information Center

Filion, Yves R.

2004-01-01

Technological growth in developed and developing countries in the 20th century has lent a great deal of importance to scientific reasoning in the management of human affairs. An important outgrowth has been the development of systems thinking to organize the workplace. The business reengineering process and the enterprise resource planning system…

Automated Simulation For Analysis And Design

NASA Technical Reports Server (NTRS)

Cantwell, E.; Shenk, Tim; Robinson, Peter; Upadhye, R.

1992-01-01

Design Assistant Workstation (DAWN) software being developed to facilitate simulation of qualitative and quantitative aspects of behavior of life-support system in spacecraft, chemical-processing plant, heating and cooling system of large building, or any of variety of systems including interacting process streams and processes. Used to analyze alternative design scenarios or specific designs of such systems. Expert system will automate part of design analysis: reason independently by simulating design scenarios and return to designer with overall evaluations and recommendations.

Designing and Implementation of Fuzzy Case-based Reasoning System on Android Platform Using Electronic Discharge Summary of Patients with Chronic Kidney Diseases

PubMed Central

Tahmasebian, Shahram; Langarizadeh, Mostafa; Ghazisaeidi, Marjan; Mahdavi-Mazdeh, Mitra

2016-01-01

Introduction: Case-based reasoning (CBR) systems are one of the effective methods to find the nearest solution to the current problems. These systems are used in various spheres as well as industry, business, and economy. The medical field is not an exception in this regard, and these systems are nowadays used in the various aspects of diagnosis and treatment. Methodology: In this study, the effective parameters were first extracted from the structured discharge summary prepared for patients with chronic kidney diseases based on data mining method. Then, through holding a meeting with experts in nephrology and using data mining methods, the weights of the parameters were extracted. Finally, fuzzy system has been employed in order to compare the similarities of current case and previous cases, and the system was implemented on the Android platform. Discussion: The data on electronic discharge records of patients with chronic kidney diseases were entered into the system. The measure of similarity was assessed using the algorithm provided in the system, and then compared with other known methods in CBR systems. Conclusion: Developing Clinical fuzzy CBR system used in Knowledge management framework for registering specific therapeutic methods, Knowledge sharing environment for experts in a specific domain and Powerful tools at the point of care. PMID:27708490

Acute asthma severity identification of expert system flow in emergency department

NASA Astrophysics Data System (ADS)

Sharif, Nurul Atikah Mohd; Ahmad, Norazura; Ahmad, Nazihah; Desa, Wan Laailatul Hanim Mat

2017-11-01

Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

Distributed semantic networks and CLIPS

NASA Technical Reports Server (NTRS)

Snyder, James; Rodriguez, Tony

1991-01-01

Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.

Expertise and category-based induction.

PubMed

Proffitt, J B; Coley, J D; Medin, D L

2000-07-01

The authors examined inductive reasoning among experts in a domain. Three types of tree experts (landscapers, taxonomists, and parks maintenance personnel) completed 3 reasoning tasks. In Experiment 1, participants inferred which of 2 novel diseases would affect "more other kinds of trees" and provided justifications for their choices. In Experiment 2, the authors used modified instructions and asked which disease would be more likely to affect "all trees." In Experiment 3, the conclusion category was eliminated altogether, and participants were asked to generate a list of other affected trees. Among these populations, typicality and diversity effects were weak to nonexistent. Instead, experts' reasoning was influenced by "local" coverage (extension of the property to members of the same folk family) and causal-ecological factors. The authors concluded that domain knowledge leads to the use of a variety of reasoning strategies not captured by current models of category-based induction.

An expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark; Lauriente, Michael; Koons, Harry C.; Gorney, David

1992-01-01

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).

Rule-based expert system for maritime anomaly detection

NASA Astrophysics Data System (ADS)

Roy, Jean

2010-04-01

Maritime domain operators/analysts have a mandate to be aware of all that is happening within their areas of responsibility. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc., and it has become more challenging in the past decade, as commercial shipping turned into a potential threat. In particular, a huge portion of the data and information made available to the operators/analysts is mundane, from maritime platforms going about normal, legitimate activities, and it is very challenging for them to detect and identify the non-mundane. To achieve such anomaly detection, they must establish numerous relevant situational facts from a variety of sensor data streams. Unfortunately, many of the facts of interest just cannot be observed; the operators/analysts thus use their knowledge of the maritime domain and their reasoning faculties to infer these facts. As they are often overwhelmed by the large amount of data and information, automated reasoning tools could be used to support them by inferring the necessary facts, ultimately providing indications and warning on a small number of anomalous events worthy of their attention. Along this line of thought, this paper describes a proof-of-concept prototype of a rule-based expert system implementing automated rule-based reasoning in support of maritime anomaly detection.

Reasoning process characteristics in the diagnostic skills of beginner, competent, and expert dentists.

PubMed

Crespo, Kathleen E; Torres, José E; Recio, María E

2004-12-01

The purpose of this study was to evaluate qualitative differences in the diagnostic reasoning process at different developmental stages of expertise. A qualitative design was used to study cognitive processes that characterize the diagnosis of oral disease at the stages of beginner (five junior students who had passed the NBDE I), competent (five GPR first-year residents), and expert dentists (five general dentists with ten or more years of experience). Individually, each participant was asked to determine the diagnosis of an oral condition based on a written clinical case, using the think aloud technique and retrospective reports. A subsequent interview was conducted to obtain the participants' diagnostic process model and pathophysiology of the case. The analysis of the verbal protocols indicated that experts referred to the patient's sociomedical context more frequently, demonstrated better organization of ideas, could determine key clinical findings, and had an ability to plan for the search of pertinent information. Fewer diagnostic hypotheses were formulated by participants who used forward reasoning, independent of the stage of development. Beginners requested additional diagnostic aids (radiographs, laboratory tests) more frequently than the competent/expert dentists. Experts recalled typical experiences with patients, while competent/beginner dentists recalled information from didactic courses. Experts evidenced cognitive diagnostic schemas that integrate pathophysiology of disease, while competent and beginner participants had not achieved this integration. We conclude that expert performance is a combination of a knowledge base, reasoning skills, and an accumulation of experiences with patients that is qualitatively different from that of competent and beginner dentists. It is important for dental education to emphasize the teaching of cognitive processes and to incorporate a wide variety of clinical experiences in addition to the teaching of disciplinary content.

Supplemental knowledge acquisition through external product interface for CLIPS

NASA Technical Reports Server (NTRS)

Saito, Tim; Ebaud, Stephen; Loftin, Bowen R.

1990-01-01

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

Expert-Novice Differences in the Understanding and Explanation of Complex Political Conflicts

ERIC Educational Resources Information Center

Jones, David K.; Read, Stephen J.

2005-01-01

We compare the structure and content of political experts' knowledge with that of novices. We were particularly interested in whether experts would show more causal and historical reasoning in explaining political events, as well as whether their knowledge was structured in the form of a narrative. Eight relative political experts (advanced…

DIAMS revisited: Taming the variety of knowledge in fault diagnosis expert systems

NASA Technical Reports Server (NTRS)

Haziza, M.; Ayache, S.; Brenot, J.-M.; Cayrac, D.; Vo, D.-P.

1994-01-01

The DIAMS program, initiated in 1986, led to the development of a prototype expert system, DIAMS-1 dedicated to the Telecom 1 Attitude and Orbit Control System, and to a near-operational system, DIAMS-2, covering a whole satellite (the Telecom 2 platform and its interfaces with the payload), which was installed in the Satellite Control Center in 1993. The refinement of the knowledge representation and reasoning is now being studied, focusing on the introduction of appropriate handling of incompleteness, uncertainty and time, and keeping in mind operational constraints. For the latest generation of the tool, DIAMS-3, a new architecture has been proposed, that enables the cooperative exploitation of various models and knowledge representations. On the same baseline, new solutions enabling higher integration of diagnostic systems in the operational environment and cooperation with other knowledge intensive systems such as data analysis, planning or procedure management tools have been introduced.

Towards a Fuzzy Expert System on Toxicological Data Quality Assessment.

PubMed

Yang, Longzhi; Neagu, Daniel; Cronin, Mark T D; Hewitt, Mark; Enoch, Steven J; Madden, Judith C; Przybylak, Katarzyna

2013-01-01

Quality assessment (QA) requires high levels of domain-specific experience and knowledge. QA tasks for toxicological data are usually performed by human experts manually, although a number of quality evaluation schemes have been proposed in the literature. For instance, the most widely utilised Klimisch scheme1 defines four data quality categories in order to tag data instances with respect to their qualities; ToxRTool2 is an extension of the Klimisch approach aiming to increase the transparency and harmonisation of the approach. Note that the processes of QA in many other areas have been automatised by employing expert systems. Briefly, an expert system is a computer program that uses a knowledge base built upon human expertise, and an inference engine that mimics the reasoning processes of human experts to infer new statements from incoming data. In particular, expert systems have been extended to deal with the uncertainty of information by representing uncertain information (such as linguistic terms) as fuzzy sets under the framework of fuzzy set theory and performing inferences upon fuzzy sets according to fuzzy arithmetic. This paper presents an experimental fuzzy expert system for toxicological data QA which is developed on the basis of the Klimisch approach and the ToxRTool in an effort to illustrate the power of expert systems to toxicologists, and to examine if fuzzy expert systems are a viable solution for QA of toxicological data. Such direction still faces great difficulties due to the well-known common challenge of toxicological data QA that "five toxicologists may have six opinions". In the meantime, this challenge may offer an opportunity for expert systems because the construction and refinement of the knowledge base could be a converging process of different opinions which is of significant importance for regulatory policy making under the regulation of REACH, though a consensus may never be reached. Also, in order to facilitate the implementation of Weight of Evidence approaches and in silico modelling proposed by REACH, there is a higher appeal of numerical quality values than nominal (categorical) ones, where the proposed fuzzy expert system could help. Most importantly, the deriving processes of quality values generated in this way are fully transparent, and thus comprehensible, for final users, which is another vital point for policy making specified in REACH. Case studies have been conducted and this report not only shows the promise of the approach, but also demonstrates the difficulties of the approach and thus indicates areas for future development. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of an Expert System for Representing Procedural Knowledge

NASA Technical Reports Server (NTRS)

Georgeff, Michael P.; Lansky, Amy L.

1985-01-01

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Building a case-based diet recommendation system without a knowledge engineer.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-02-01

We present a new approach to the effective development of menu construction systems that allow to automatically construct a menu that is strongly tailored to the individual requirements and food preferences of a client. In hospitals and other health care institutions dietitians develop diets for clients which need to change their eating habits. Many clients have special needs in regards to their medical conditions, cultural backgrounds, or special levels of nutrient requirements for better recovery from diseases or surgery, etc. Existing computer support for this task is insufficient-many diets are not specifically tailored for the client's needs or require substantial time of a dietitian to be manually developed. Our approach is based on case-based reasoning, an artificial intelligence technique that finds increasing entry into industrial practice. Our approach goes beyond the traditional case-based reasoning (CBR) approach by allowing an incremental improvement of the system's competency during routine use of the system. The improvement of the system takes place through a direct expert user-system interaction while the expert is accomplishing their tasks of constructing a diet for a given client. Whenever the system performs unsatisfactorily, the expert will need to modify the system-produced diet 'manually', i.e. by entering the desired modifications into the system. Our implemented system, menu construction using an incremental knowledge acquisition system (MIKAS), asks the expert for simple explanations for each of the manual actions he/she takes and incorporates the explanations automatically into its knowledge base (KB) so that the system will perform these manually conducted actions automatically at the next occasion. We present MIKAS and discuss the results of our case study. While still being a prototype, the senior clinical dietitian involved in our evaluation studies judges the approach to have considerable potential to improve the daily routine of hospital dietitians as well as to improve the average quality of the dietary advice given to patients within the limited available time for dietary consultations. Our approach opens up a new avenue towards building highly specialised CBR systems in a more cost-effective way. Hence, our approach promises to allow a significantly more widespread development and practical deployment of CBR systems in a large variety of application domains including many medical applications.

A memory efficient user interface for CLIPS micro-computer applications

NASA Technical Reports Server (NTRS)

Sterle, Mark E.; Mayer, Richard J.; Jordan, Janice A.; Brodale, Howard N.; Lin, Min-Jin

1990-01-01

The goal of the Integrated Southern Pine Beetle Expert System (ISPBEX) is to provide expert level knowledge concerning treatment advice that is convenient and easy to use for Forest Service personnel. ISPBEX was developed in CLIPS and delivered on an IBM PC AT class micro-computer, operating with an MS/DOS operating system. This restricted the size of the run time system to 640K. In order to provide a robust expert system, with on-line explanation, help, and alternative actions menus, as well as features that allow the user to back up or execute 'what if' scenarios, a memory efficient menuing system was developed to interface with the CLIPS programs. By robust, we mean an expert system that (1) is user friendly, (2) provides reasonable solutions for a wide variety of domain specific problems, (3) explains why some solutions were suggested but others were not, and (4) provides technical information relating to the problem solution. Several advantages were gained by using this type of user interface (UI). First, by storing the menus on the hard disk (instead of main memory) during program execution, a more robust system could be implemented. Second, since the menus were built rapidly, development time was reduced. Third, the user may try a new scenario by backing up to any of the input screens and revising segments of the original input without having to retype all the information. And fourth, asserting facts from the menus provided for a dynamic and flexible fact base. This UI technology has been applied successfully in expert systems applications in forest management, agriculture, and manufacturing. This paper discusses the architecture of the UI system, human factors considerations, and the menu syntax design.

Undermining Reasonableness: Expert Testimony in a Case Involving a Battered Woman Who Kills

ERIC Educational Resources Information Center

Terrance, Cheryl; Matheson, Kimberly

2003-01-01

Student participants (N = 316) viewed a videotaped simulated case involving a woman who had entered a self-defense plea in the shooting death of her abusive husband. As successful claims of self-defense rest on the portrayal of a defendant who has responded reasonably to his/her situation, the implications of various forms of expert testimony in…

Do Expert Clinical Teachers Have a Shared Understanding of What Constitutes a Competent Reasoning Performance in Case-Based Teaching?

ERIC Educational Resources Information Center

Gauthier, Geneviève; Lajoie, Susanne P.

2014-01-01

To explore the assessment challenge related to case based learning we study how experienced clinical teachers--i.e., those who regularly teach and assess case-based learning--conceptualize the notion of competent reasoning performance for specific teaching cases. Through an in-depth qualitative case study of five expert teachers, we investigate…

You Get What You Need: An Examination of Purpose-Based Inheritance Reasoning in Undergraduates, Preschoolers, and Biological Experts

ERIC Educational Resources Information Center

Ware, Elizabeth A.; Gelman, Susan A.

2014-01-01

This set of seven experiments examines reasoning about the inheritance and acquisition of physical properties in preschoolers, undergraduates, and biology experts. Participants (N = 390) received adoption vignettes in which a baby animal was born to one parent but raised by a biologically unrelated parent, and they judged whether the offspring…

Vaccine Rejecting Parents' Engagement With Expert Systems That Inform Vaccination Programs.

PubMed

Attwell, Katie; Leask, Julie; Meyer, Samantha B; Rokkas, Philippa; Ward, Paul

2017-03-01

In attempting to provide protection to individuals and communities, childhood immunization has benefits that far outweigh disease risks. However, some parents decide not to immunize their children with some or all vaccines for reasons including lack of trust in governments, health professionals, and vaccine manufacturers. This article employs a theoretical analysis of trust and distrust to explore how twenty-seven parents with a history of vaccine rejection in two Australian cities view the expert systems central to vaccination policy and practice. Our data show how perceptions of the profit motive generate distrust in the expert systems pertaining to vaccination. Our participants perceived that pharmaceutical companies had a pernicious influence over the systems driving vaccination: research, health professionals, and government. Accordingly, they saw vaccine recommendations in conflict with the interests of their child and "the system" underscored by malign intent, even if individual representatives of this system were not equally tainted. This perspective was common to parents who declined all vaccines and those who accepted some. We regard the differences between these parents-and indeed the differences between vaccine decliners and those whose Western medical epistemology informs reflexive trust-as arising from the internalization of countering views, which facilitates nuance.

Remedial action assessment system: Decision support for environmental cleanup

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pennock, K.A.; Bohn, S.; Franklin, A.L.

1991-11-01

A large number of hazardous waste sites across the United States await treatment. Waste sites can be physically complex entities composed of multiple, possibly interacting contaminants distributed throughout one or more media. The sites may be active as well with contaminants escaping through one or more potential escape paths. Treatment of these sites requires a long and costly commitment involving the coordination of activities among several waste treatment professionals. In order to reduce the cost and time required for the specification of treatment at these waste sites. The Remedial Action Assessment System (RAAS) was proposed. RAAS is an automated informationmore » management system which utilizes a combination of expert reasoning and numerical models to produce the combinations of treatment technologies, known as treatment trains, which satisfy the treatment objectives of a particular site. In addition, RAAS supports the analysis of these trains with regard to effectiveness and cost so that the viable treatment trains can be measured against each other. The Remedial Action Assessment System is a hybrid system designed and constructed using object-oriented tools and techniques. RAAS is advertised as a hybrid system because it combines, in integral fashion, numerical computing (primarily quantitative models) with expert system reasoning. An object-oriented approach was selected due to many of its inherent advantages, among these the naturalness of modeling physical objects and processes.« less

29 CFR 18.705 - Disclosure of facts or data underlying expert opinion.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 1 2013-07-01 2013-07-01 false Disclosure of facts or data underlying expert opinion. 18... Testimony § 18.705 Disclosure of facts or data underlying expert opinion. The expert may testify in terms of opinion or inference and give reasons therefor without prior disclosure of the underlying facts or data...

29 CFR 18.705 - Disclosure of facts or data underlying expert opinion.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 1 2011-07-01 2011-07-01 false Disclosure of facts or data underlying expert opinion. 18... Testimony § 18.705 Disclosure of facts or data underlying expert opinion. The expert may testify in terms of opinion or inference and give reasons therefor without prior disclosure of the underlying facts or data...

29 CFR 18.705 - Disclosure of facts or data underlying expert opinion.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 1 2014-07-01 2013-07-01 true Disclosure of facts or data underlying expert opinion. 18... Testimony § 18.705 Disclosure of facts or data underlying expert opinion. The expert may testify in terms of opinion or inference and give reasons therefor without prior disclosure of the underlying facts or data...

29 CFR 18.705 - Disclosure of facts or data underlying expert opinion.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 1 2010-07-01 2010-07-01 true Disclosure of facts or data underlying expert opinion. 18... Testimony § 18.705 Disclosure of facts or data underlying expert opinion. The expert may testify in terms of opinion or inference and give reasons therefor without prior disclosure of the underlying facts or data...

29 CFR 18.705 - Disclosure of facts or data underlying expert opinion.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 1 2012-07-01 2012-07-01 false Disclosure of facts or data underlying expert opinion. 18... Testimony § 18.705 Disclosure of facts or data underlying expert opinion. The expert may testify in terms of opinion or inference and give reasons therefor without prior disclosure of the underlying facts or data...

Mixed-initiative control of intelligent systems

NASA Technical Reports Server (NTRS)

Borchardt, G. C.

1987-01-01

Mixed-initiative user interfaces provide a means by which a human operator and an intelligent system may collectively share the task of deciding what to do next. Such interfaces are important to the effective utilization of real-time expert systems as assistants in the execution of critical tasks. Presented here is the Incremental Inference algorithm, a symbolic reasoning mechanism based on propositional logic and suited to the construction of mixed-initiative interfaces. The algorithm is similar in some respects to the Truth Maintenance System, but replaces the notion of 'justifications' with a notion of recency, allowing newer values to override older values yet permitting various interested parties to refresh these values as they become older and thus more vulnerable to change. A simple example is given of the use of the Incremental Inference algorithm plus an overview of the integration of this mechanism within the SPECTRUM expert system for geological interpretation of imaging spectrometer data.

Demonstrating artificial intelligence for space systems - Integration and project management issues

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Difilippo, Denise M.

1990-01-01

As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

Construct validity of the Health Science Reasoning Test.

PubMed

Huhn, Karen; Black, Lisa; Jensen, Gail M; Deutsch, Judith E

2011-01-01

The aim of this study was to evaluate the construct validity of the Health Science Reasoning Test (HSRT) by determining if the test could discriminate between expert and novice physical therapists' critical-thinking skills. Experts identified from a random list of certified clinical specialists and students in the first year of their physical therapy education from two physical therapy programs completed the HSRT. Experts (n = 73) had a higher total HSRT score (mean 24.06, SD 3.92) than the novices (n = 79) (mean 22.49, SD 3.2), with the difference being statistically significant t (148) = 2.67, p = 0.008. The HSRT total score discriminated between expert and novice critical-thinking skills, therefore establishing construct validity. To our knowledge, this is the first study to compare expert and novice performance on a standardized test. The opportunity to have a tool that provides evidence of students' critical thinking skills could be helpful for educators and students. The test results could aid in identifying areas of students' strengths and weaknesses, thereby enabling targeted remediation to improve critical thinking skills, which are key factors in clinical reasoning, a necessary skill for effective physical therapy practice.

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

N Reasons Why Production-Rules are Insufficient Models for Expert System Knowledge Representation Schemes

DTIC Science & Technology

1991-02-01

3 2.2 Hybrid Rule/Fact Schemas .............................................................. 3 3 THE LIMITATIONS OF RULE BASED KNOWLEDGE...or hybrid rule/fact schemas. 2 UNCLASSIFIED .WA UNCLASSIFIED ERL-0520-RR 2.1 Propositional Logic The simplest form of production-rules are based upon...requirements which may lead to poor system performance. 2.2 Hybrid Rule/Fact Schemas Hybrid rule/fact relationships (also known as Predicate Calculus ) have

Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.

DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning

PubMed Central

Golobardes, Elisabet; Corral, Guiomar; Puig, Susana; Malvehy, Josep

2014-01-01

The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosis has become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration of several multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis. PMID:24578629

Planning bioinformatics workflows using an expert system.

PubMed

Chen, Xiaoling; Chang, Jeffrey T

2017-04-15

Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. https://github.com/jefftc/changlab. jeffrey.t.chang@uth.tmc.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Planning bioinformatics workflows using an expert system

PubMed Central

Chen, Xiaoling; Chang, Jeffrey T.

2017-01-01

Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: jeffrey.t.chang@uth.tmc.edu PMID:28052928

Assistant for Analyzing Tropical-Rain-Mapping Radar Data

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

A document is defined that describes an approach for a Tropical Rain Mapping Radar Data System (TDS). TDS is composed of software and hardware elements incorporating a two-frequency spaceborne radar system for measuring tropical precipitation. The TDS would be used primarily in generating data products for scientific investigations. The most novel part of the TDS would be expert-system software to aid in the selection of algorithms for converting raw radar-return data into such primary observables as rain rate, path-integrated rain rate, and surface backscatter. The expert-system approach would address the issue that selection of algorithms for processing the data requires a significant amount of preprocessing, non-intuitive reasoning, and heuristic application, making it infeasible, in many cases, to select the proper algorithm in real time. In the TDS, tentative selections would be made to enable conversions in real time. The expert system would remove straightforwardly convertible data from further consideration, and would examine ambiguous data, performing analysis in depth to determine which algorithms to select. Conversions performed by these algorithms, presumed to be correct, would be compared with the corresponding real-time conversions. Incorrect real-time conversions would be updated using the correct conversions.

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

PubMed

Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

2015-11-30

Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.

Monte Carlo simulation of expert judgments on human errors in chemical analysis--a case study of ICP-MS.

PubMed

Kuselman, Ilya; Pennecchi, Francesca; Epstein, Malka; Fajgelj, Ales; Ellison, Stephen L R

2014-12-01

Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors. Copyright © 2014 Elsevier B.V. All rights reserved.

Cancer Battles and the Sleep of Reason policy and science need not be related.

PubMed

Bennett, David

2003-01-01

Cancer Battles and the Sleep of Reason is an inquiry into the role of scientific experts in environmental health policy-making. The article first establishes two propositions: that there is no necessary relationship between science and environmental health policy; and that risk assessment is not the only science of environmental health. It then asks the question: why should policy-makers consult the scientific experts? If experts are to be consulted, there will have to be some way of grading experts as to the quality of their advice and their usefulness to policy-makers. A mode of grading experts is provided in Environmental Cancer--A Political Disease? by S. Robert Lichter and Stanley Rothman. But the arguments in this book are shown to be worthless; the book fails to address the underlying issue of why the experts should be consulted at all. The article concludes that experts are to be consulted whenever policy-makers consider their advice to be essential or useful. There is nothing in the scientific disciplines that entrenches them in the policymaking process; the opinions of scientific experts have no special place in environmental health policy.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferrada, J.J.; Osborne-Lee, I.W.; Grizzaffi, P.A.

Expert systems are known to be useful in capturing expertise and applying knowledge to chemical engineering problems such as diagnosis, process control, process simulation, and process advisory. However, expert system applications are traditionally limited to knowledge domains that are heuristic and involve only simple mathematics. Neural networks, on the other hand, represent an emerging technology capable of rapid recognition of patterned behavior without regard to mathematical complexity. Although useful in problem identification, neural networks are not very efficient in providing in-depth solutions and typically do not promote full understanding of the problem or the reasoning behind its solutions. Hence, applicationsmore » of neural networks have certain limitations. This paper explores the potential for expanding the scope of chemical engineering areas where neural networks might be utilized by incorporating expert systems and neural networks into the same application, a process called hybridization. In addition, hybrid applications are compared with those using more traditional approaches, the results of the different applications are analyzed, and the feasibility of converting the preliminary prototypes described herein into useful final products is evaluated. 12 refs., 8 figs.« less

Space station automation: the role of robotics and artificial intelligence (Invited Paper)

NASA Astrophysics Data System (ADS)

Park, W. T.; Firschein, O.

1985-12-01

Automation of the space station is necessary to make more effective use of the crew, to carry out repairs that are impractical or dangerous, and to monitor and control the many space station subsystems. Intelligent robotics and expert systems play a strong role in automation, and both disciplines are highly dependent on a common artificial intelligence (Al) technology base. The AI technology base provides the reasoning and planning capabilities needed in robotic tasks, such as perception of the environment and planning a path to a goal, and in expert systems tasks, such as control of subsystems and maintenance of equipment. This paper describes automation concepts for the space station, the specific robotic and expert systems required to attain this automation, and the research and development required. It also presents an evolutionary development plan that leads to fully automatic mobile robots for servicing satellites. Finally, we indicate the sequence of demonstrations and the research and development needed to confirm the automation capabilities. We emphasize that advanced robotics requires AI, and that to advance, AI needs the "real-world" problems provided by robotics.

Software Assists in Responding to Anomalous Conditions

NASA Technical Reports Server (NTRS)

James, Mark; Kronbert, F.; Weiner, A.; Morgan, T.; Stroozas, B.; Girouard, F.; Hopkins, A.; Wong, L.; Kneubuhl, J.; Malina, R.

2004-01-01

Fault Induced Document Retrieval Officer (FIDO) is a computer program that reduces the need for a large and costly team of engineers and/or technicians to monitor the state of a spacecraft and associated ground systems and respond to anomalies. FIDO includes artificial-intelligence components that imitate the reasoning of human experts with reference to a knowledge base of rules that represent failure modes and to a database of engineering documentation. These components act together to give an unskilled operator instantaneous expert assistance and access to information that can enable resolution of most anomalies, without the need for highly paid experts. FIDO provides a system state summary (a configurable engineering summary) and documentation for diagnosis of a potentially failing component that might have caused a given error message or anomaly. FIDO also enables high-level browsing of documentation by use of an interface indexed to the particular error message. The collection of available documents includes information on operations and associated procedures, engineering problem reports, documentation of components, and engineering drawings. FIDO also affords a capability for combining information on the state of ground systems with detailed, hierarchically-organized, hypertext- enabled documentation.

Governing Schools for Productivity. The Productivity for Results Series No. 4

ERIC Educational Resources Information Center

Hill, Paul T.

2014-01-01

The lack of productivity of school systems stems from a number of reasons, including the way in which schools are governed. The author explains in this paper that policies from on high often work against campuses being more productive. His list includes state policies that stop districts from hiring experts to teach subjects that other educators…

Learning How the Electron Transport Chain Works: Independent and Interactive Effects of Instructional Strategies and Learners' Characteristics

ERIC Educational Resources Information Center

Darabi, Aubteen; Arrastia-Lloyd, Meagan C.; Nelson, David W.; Liang, Xinya; Farrell, Jennifer

2015-01-01

In order to develop an expert-like mental model of complex systems, causal reasoning is essential. This study examines the differences between forward and backward instructional strategies in terms of efficiency, students' learning and progression of their mental models of the electronic transport chain in an undergraduate metabolism course…

Working memory, reasoning, and expertise in medicine-insights into their relationship using functional neuroimaging.

PubMed

Hruska, Pam; Krigolson, Olav; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Hecker, Kent G

2016-12-01

Clinical reasoning is dependent upon working memory (WM). More precisely, during the clinical reasoning process stored information within long-term memory is brought into WM to facilitate the internal deliberation that affords a clinician the ability to reason through a case. In the present study, we examined the relationship between clinical reasoning and WM while participants read clinical cases with functional magnetic resonance imaging (fMRI). More specifically, we examined the impact of clinical case difficulty (easy, hard) and clinician level of expertise (2nd year medical students, senior gastroenterologists) on neural activity within regions of cortex associated with WM (i.e., the prefrontal cortex) during the reasoning process. fMRI was used to scan ten second-year medical students and ten practicing gastroenterologists while they reasoned through sixteen clinical cases [eight straight forward (easy) and eight complex (hard)] during a single 1-h scanning session. Within-group analyses contrasted the easy and hard cases which were then subsequently utilized for a between-group analysis to examine effects of expertise (novice > expert, expert > novice). Reading clinical cases evoked multiple neural activations in occipital, prefrontal, parietal, and temporal cortical regions in both groups. Importantly, increased activation in the prefrontal cortex in novices for both easy and hard clinical cases suggests novices utilize WM more so than experts during clinical reasoning. We found that clinician level of expertise elicited differential activation of regions of the human prefrontal cortex associated with WM during clinical reasoning. This suggests there is an important relationship between clinical reasoning and human WM. As such, we suggest future models of clinical reasoning take into account that the use of WM is not consistent throughout all clinical reasoning tasks, and that memory structure may be utilized differently based on level of expertise.

Automated eddy current analysis of materials

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1990-01-01

This research effort focused on the use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures. A major emphasis was on incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) has been a goal in the overall concept and is essential for the final implementation for expert system interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of the flaw can be performed. In eddy current or any other expert systems used to analyze signals in real time in a production environment, it is important to simplify computational procedures as much as possible. For that reason, we have chosen to use the measured resistance and reactance values for the preliminary aspects of this work. A simple computation, such as phase angle of the signal, is certainly within the real time processing capability of the computer system. In the work described here, there is a balance between physical measurements and finite element calculations of those measurements. The goal is to evolve into the most cost effective procedures for maintaining the correctness of the knowledge base.

Employing UMLS for generating hints in a tutoring system for medical problem-based learning.

PubMed

Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan

2012-06-01

While problem-based learning has become widely popular for imparting clinical reasoning skills, the dynamics of medical PBL require close attention to a small group of students, placing a burden on medical faculty, whose time is over taxed. Intelligent tutoring systems (ITSs) offer an attractive means to increase the amount of facilitated PBL training the students receive. But typical intelligent tutoring system architectures make use of a domain model that provides a limited set of approved solutions to problems presented to students. Student solutions that do not match the approved ones, but are otherwise partially correct, receive little acknowledgement as feedback, stifling broader reasoning. Allowing students to creatively explore the space of possible solutions is exactly one of the attractive features of PBL. This paper provides an alternative to the traditional ITS architecture by using a hint generation strategy that leverages a domain ontology to provide effective feedback. The concept hierarchy and co-occurrence between concepts in the domain ontology are drawn upon to ascertain partial correctness of a solution and guide student reasoning towards a correct solution. We describe the strategy incorporated in METEOR, a tutoring system for medical PBL, wherein the widely available UMLS is deployed and represented as the domain ontology. Evaluation of expert agreement with system generated hints on a 5-point likert scale resulted in an average score of 4.44 (Spearman's ρ=0.80, p<0.01). Hints containing partial correctness feedback scored significantly higher than those without it (Mann Whitney, p<0.001). Hints produced by a human expert received an average score of 4.2 (Spearman's ρ=0.80, p<0.01). Copyright © 2012 Elsevier Inc. All rights reserved.

A Preliminary Investigation on the Application of Robotics to Missile Fire Control.

DTIC Science & Technology

1983-11-01

application. Even this is a broad area, but it is one in which Okhe general theories and concepts of robo - tics and/or artificial intelligence can be...K::. 3. Expert Advisors .J1. %4. Data Assimilation and Access Aids 5. Handling Support Systems 6. Support Systems 7...appears, therefore, that a robo - tic forward observer can be manufactured in quantities for a reasonable cost when compared to the cost of training

Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data

NASA Astrophysics Data System (ADS)

Fard, Amin Milani

Knowledge extraction from distributed database systems, have been investigated during past decade in order to analyze billions of information records. In this work a competitive deduction approach in a heterogeneous data grid environment is proposed using classic data mining and statistical methods. By applying a game theory concept in a multi-agent model, we tried to design a policy for hierarchical knowledge discovery and inference fusion. To show the system run, a sample multi-expert system has also been developed.

Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions

NASA Technical Reports Server (NTRS)

Zadeh, L. A.

1985-01-01

A fuzzy syllogism in fuzzy logic is defined to be an inference schema in which the major premise, the minor premise and the conclusion are propositions containing fuzzy quantifiers. A basic fuzzy syllogism in fuzzy logic is the intersection/product syllogism. Several other basic syllogisms are developed that may be employed as rules of combination of evidence in expert systems. Among these is the consequent conjunction syllogism. Furthermore, it is shown that syllogistic reasoning in fuzzy logic provides a basis for reasoning with dispositions; that is, with propositions that are preponderantly but not necessarily always true. It is also shown that the concept of dispositionality is closely related to the notion of usuality and serves as a basis for what might be called a theory of usuality - a theory which may eventually provide a computational framework for commonsense reasoning.

Observable phenomena that reveal medical students' clinical reasoning ability during expert assessment of their history taking: a qualitative study.

PubMed

Haring, Catharina M; Cools, Bernadette M; van Gurp, Petra J M; van der Meer, Jos W M; Postma, Cornelis T

2017-08-29

During their clerkships, medical students are meant to expand their clinical reasoning skills during their patient encounters. Observation of these encounters could reveal important information on the students' clinical reasoning abilities, especially during history taking. A grounded theory approach was used to analyze what expert physicians apply as indicators in their assessment of medical students' diagnostic reasoning abilities during history taking. Twelve randomly selected clinical encounter recordings of students at the end of the internal medicine clerkships were observed by six expert assessors, who were prompted to formulate their assessment criteria in a think-aloud procedure. These formulations were then analyzed to identify the common denominators and leading principles. The main indicators of clinical reasoning ability were abstracted from students' observable acts during history taking in the encounter. These were: taking control, recognizing and responding to relevant information, specifying symptoms, asking specific questions that point to pathophysiological thinking, placing questions in a logical order, checking agreement with patients, summarizing and body language. In addition, patients' acts and the course, result and efficiency of the conversation were identified as indicators of clinical reasoning, whereas context, using self as a reference, and emotion/feelings were identified by the clinicians as variables in their assessment of clinical reasoning. In observing and assessing clinical reasoning during history taking by medical students, general and specific phenomena to be used as indicators for this process could be identified. These phenomena can be traced back to theories on the development and the process of clinical reasoning.

International recommendations for national patient safety incident reporting systems: an expert Delphi consensus-building process.

PubMed

Howell, Ann-Marie; Burns, Elaine M; Hull, Louise; Mayer, Erik; Sevdalis, Nick; Darzi, Ara

2017-02-01

Patient safety incident reporting systems (PSRS) have been established for over a decade, but uncertainty remains regarding the role that they can and ought to play in quantifying healthcare-related harm and improving care. To establish international, expert consensus on the purpose of PSRS regarding monitoring and learning from incidents and developing recommendations for their future role. After a scoping review of the literature, semi-structured interviews with experts in PSRS were conducted. Based on these findings, a survey-based questionnaire was developed and subsequently completed by a larger expert panel. Using a Delphi approach, consensus was reached regarding the ideal role of PSRSs. Recommendations for best practice were devised. Forty recommendations emerged from the Delphi procedure on the role and use of PSRS. Experts agreed reporting system should not be used as an epidemiological tool to monitor the rate of harm over time or to appraise the relative safety of hospitals. They agreed reporting is a valuable mechanism for identifying organisational safety needs. The benefit of a national system was clear with respect to medication error, device failures, hospital-acquired infections and never events as these problems often require solutions at a national level. Experts recommended training for senior healthcare professionals in incident investigation. Consensus recommendation was for hospitals to take responsibility for creating safety solutions locally that could be shared nationally. We obtained reasonable consensus among experts on aims and specifications of PSRS. This information can be used to reflect on existing and future PSRS, and their role within the wider patient safety landscape. The role of PSRS as instruments for learning needs to be elaborated and developed further internationally. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

An Intelligent computer-aided tutoring system for diagnosing anomalies of spacecraft in operation

NASA Technical Reports Server (NTRS)

Rolincik, Mark; Lauriente, Michael; Koons, Harry C.; Gorney, David

1993-01-01

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Categorization and Reasoning among Tree Experts: Do All Roads Lead to Rome?

ERIC Educational Resources Information Center

Medin, Douglas L.; And Others

1997-01-01

Results of two experiments concerned with categorization among different types of tree experts (4 taxonomists, 10 landscape workers, and 10 park maintenance employees in the first experiment and a subset of these experts in the second) show a pattern of similarities and differences. Implications for theories of categorization are discussed. (SLD)

StarPlan: A model-based diagnostic system for spacecraft

NASA Technical Reports Server (NTRS)

Heher, Dennis; Pownall, Paul

1990-01-01

The Sunnyvale Division of Ford Aerospace created a model-based reasoning capability for diagnosing faults in space systems. The approach employs reasoning about a model of the domain (as it is designed to operate) to explain differences between expected and actual telemetry; i.e., to identify the root cause of the discrepancy (at an appropriate level of detail) and determine necessary corrective action. A development environment, named Paragon, was implemented to support both model-building and reasoning. The major benefit of the model-based approach is the capability for the intelligent system to handle faults that were not anticipated by a human expert. The feasibility of this approach for diagnosing problems in a spacecraft was demonstrated in a prototype system, named StarPlan. Reasoning modules within StarPlan detect anomalous telemetry, establish goals for returning the telemetry to nominal values, and create a command plan for attaining the goals. Before commands are implemented, their effects are simulated to assure convergence toward the goal. After the commands are issued, the telemetry is monitored to assure that the plan is successful. These features of StarPlan, along with associated concerns, issues and future directions, are discussed.

Consensus Theory in Expert Systems: An Adaptive Inference Framework and Application to Image Understanding

DTIC Science & Technology

1988-12-01

argument schema based on the one devel- oped by Toulmin et al. (1984). In Toulmin’s schema (Figure 4-2), a claim, or 3 conclusion whose merits we are seeking...probability judgment. Cognitive Science, 1985, 9, 309-339. Toulmin , S., Rieke, R., and Janik, A. An introduction to reasoning (2nd Edition). NY

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

1991-01-01

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

An expert system for integrated structural analysis and design optimization for aerospace structures

NASA Technical Reports Server (NTRS)

1992-01-01

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

An expert system for integrated structural analysis and design optimization for aerospace structures

NASA Astrophysics Data System (ADS)

1992-04-01

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

Diagnosis and sensor validation through knowledge of structure and function

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.; Jamieson, John R.; Delaune, Carl I.

1987-01-01

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Knowledge acquisition for case-based reasoning systems

NASA Technical Reports Server (NTRS)

Riesbeck, Christopher K.

1988-01-01

Case-based reasoning (CBR) is a simple idea: solve new problems by adapting old solutions to similar problems. The CBR approach offers several potential advantages over rule-based reasoning: rules are not combined blindly in a search for solutions, solutions can be explained in terms of concrete examples, and performance can improve automatically as new problems are solved and added to the case library. Moving CBR for the university research environment to the real world requires smooth interfaces for getting knowledge from experts. Described are the basic elements of an interface for acquiring three basic bodies of knowledge that any case-based reasoner requires: the case library of problems and their solutions, the analysis rules that flesh out input problem specifications so that relevant cases can be retrieved, and the adaptation rules that adjust old solutions to fit new problems.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts.

PubMed

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam; Zurek, Tomasz

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts

PubMed Central

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains. PMID:26495435

Assessing ethical problem solving by reasoning rather than decision making.

PubMed

Tsai, Tsuen-Chiuan; Harasym, Peter H; Coderre, Sylvain; McLaughlin, Kevin; Donnon, Tyrone

2009-12-01

The assessment of ethical problem solving in medicine has been controversial and challenging. The purposes of this study were: (i) to create a new instrument to measure doctors' decisions on and reasoning approach towards resolving ethical problems; (ii) to evaluate the scores generated by the new instrument for their reliability and validity, and (iii) to compare doctors' ethical reasoning abilities between countries and among medical students, residents and experts. This study used 15 clinical vignettes and the think-aloud method to identify the processes and components involved in ethical problem solving. Subjects included volunteer ethics experts, postgraduate Year 2 residents and pre-clerkship medical students. The interview data were coded using the instruments of the decision score and Ethical Reasoning Inventory (ERI). The ERI assessed the quality of ethical reasoning for a particular case (Part I) and for an individual globally across all the vignettes (Part II). There were 17 Canadian and 32 Taiwanese subjects. Based on the Canadian standard, the decision scores between Taiwanese and Canadian subjects differed significantly, but made no discrimination among the three levels of expertise. Scores on the ERI Parts I and II, which reflect doctors' reasoning quality, differed between countries and among different levels of expertise in Taiwan, providing evidence of construct validity. In addition, experts had a greater organised knowledge structure and considered more relevant variables in the process of arriving at ethical decisions than did residents or students. The reliability of ERI scores was 0.70-0.99 on Part I and 0.75-0.80 on Part II. Expertise in solving ethical problems could not be differentiated by the decisions made, but could be differentiated according to the reasoning used to make those decisions. The difference between Taiwanese and Canadian experts suggests that cultural considerations come into play in the decisions that are made in the course of providing humane care to patients.

Battered women who kill: the impact of expert testimony and empathy induction in the courtroom.

PubMed

Plumm, Karyn M; Terrance, Cheryl A

2009-02-01

Mock jurors (N = 312) viewed a simulated trial involving a woman, charged with the murder of her abusive husband, entering a plea of not guilty by reason of self-defense. Expert testimony was varied using battered woman syndrome, social agency framework, or no expert testimony. Within expert testimony conditions, jurors were presented with opening and closing statements either including or not including instructions aimed at inducing empathy. Results indicate differences in gender and expert testimony for ratings of guilt as well as differences in gender, expert testimony, and empathy induction for perceptions of the defendant.

Explanation and the Theory of Expert Problem Solving

DTIC Science & Technology

1990-02-01

specified output, Our work has aimed to identify the individual generic tasks, to analyze them properly, and to clarify their relationships to more...coverage of hypotheses must be tractable. that there cannot be many incompatibility relationships or cancellation effects between individual hypotheses. and...no necessary relationship between this justificatory argument and the actual reasoning that produced the solution. In Wick’s system the explanation

An architecture for heuristic control of real-time processes

NASA Technical Reports Server (NTRS)

Raulefs, P.; Thorndyke, P. W.

1987-01-01

Abstract Process management combines complementary approaches of heuristic reasoning and analytical process control. Management of a continuous process requires monitoring the environment and the controlled system, assessing the ongoing situation, developing and revising planned actions, and controlling the execution of the actions. For knowledge-intensive domains, process management entails the potentially time-stressed cooperation among a variety of expert systems. By redesigning a blackboard control architecture in an object-oriented framework, researchers obtain an approach to process management that considerably extends blackboard control mechanisms and overcomes limitations of blackboard systems.

Representing Mutually Exclusive Knowledge in a Property Hierarchy for a Reasoning System in Clinical Gynecology

PubMed Central

Small, Steven L.; Muechler, Eberhard K.

1985-01-01

The education and practice of clinical medicine can benefit significantly from the use of computational assistants. This article describes the development of a prototype system called SURGES (Strong/University of Rochester Gynecological Expert System) for representing medical knowledge and then applying this knowledge to suggest diagnostic procedures in medical gynecology. The paper focuses on the representation technique of property inheritance, which facilitates the simple common sense reasoning required to enable execution of the more complex medical inferences. Such common sense can be viewed as a collection mundane inferences, which are the simple conclusions drawn from knowledge that an exclusive or (XOR) relation (i.e., mutual exclusion) holds among a number of facts. The paper discusses the use of a property hierarchy for this purpose and shows how it simplifies knowledge representation in medical artificial intelligence (AIM) computer systems.

Defining the Correctness of a Diagnosis: Differential Judgments and Expert Knowledge

ERIC Educational Resources Information Center

Kanter, Steven L.; Brosenitsch, Teresa A.; Mahoney, John F.; Staszewski, James

2010-01-01

Approaches that use a simulated patient case to study and assess diagnostic reasoning usually use the correct diagnosis of the case as a measure of success and as an anchor for other measures. Commonly, the correctness of a diagnosis is determined by the judgment of one or more experts. In this study, the consistency of experts' judgments of the…

Automatic determination of fault effects on aircraft functionality

NASA Technical Reports Server (NTRS)

Feyock, Stefan

1989-01-01

The problem of determining the behavior of physical systems subsequent to the occurrence of malfunctions is discussed. It is established that while it was reasonable to assume that the most important fault behavior modes of primitive components and simple subsystems could be known and predicted, interactions within composite systems reached levels of complexity that precluded the use of traditional rule-based expert system techniques. Reasoning from first principles, i.e., on the basis of causal models of the physical system, was required. The first question that arises is, of course, how the causal information required for such reasoning should be represented. The bond graphs presented here occupy a position intermediate between qualitative and quantitative models, allowing the automatic derivation of Kuipers-like qualitative constraint models as well as state equations. Their most salient feature, however, is that entities corresponding to components and interactions in the physical system are explicitly represented in the bond graph model, thus permitting systematic model updates to reflect malfunctions. Researchers show how this is done, as well as presenting a number of techniques for obtaining qualitative information from the state equations derivable from bond graph models. One insight is the fact that one of the most important advantages of the bond graph ontology is the highly systematic approach to model construction it imposes on the modeler, who is forced to classify the relevant physical entities into a small number of categories, and to look for two highly specific types of interactions among them. The systematic nature of bond graph model construction facilitates the process to the point where the guidelines are sufficiently specific to be followed by modelers who are not domain experts. As a result, models of a given system constructed by different modelers will have extensive similarities. Researchers conclude by pointing out that the ease of updating bond graph models to reflect malfunctions is a manifestation of the systematic nature of bond graph construction, and the regularity of the relationship between bond graph models and physical reality.

Script-theory virtual case: A novel tool for education and research.

PubMed

Hayward, Jake; Cheung, Amandy; Velji, Alkarim; Altarejos, Jenny; Gill, Peter; Scarfe, Andrew; Lewis, Melanie

2016-11-01

Context/Setting: The script theory of diagnostic reasoning proposes that clinicians evaluate cases in the context of an "illness script," iteratively testing internal hypotheses against new information eventually reaching a diagnosis. We present a novel tool for teaching diagnostic reasoning to undergraduate medical students based on an adaptation of script theory. We developed a virtual patient case that used clinically authentic audio and video, interactive three-dimensional (3D) body images, and a simulated electronic medical record. Next, we used interactive slide bars to record respondents' likelihood estimates of diagnostic possibilities at various stages of the case. Responses were dynamically compared to data from expert clinicians and peers. Comparative frequency distributions were presented to the learner and final diagnostic likelihood estimates were analyzed. Detailed student feedback was collected. Over two academic years, 322 students participated. Student diagnostic likelihood estimates were similar year to year, but were consistently different from expert clinician estimates. Student feedback was overwhelmingly positive: students found the case was novel, innovative, clinically authentic, and a valuable learning experience. We demonstrate the successful implementation of a novel approach to teaching diagnostic reasoning. Future study may delineate reasoning processes associated with differences between novice and expert responses.

Workflow Agents vs. Expert Systems: Problem Solving Methods in Work Systems Design

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Seah, Chin

2009-01-01

During the 1980s, a community of artificial intelligence researchers became interested in formalizing problem solving methods as part of an effort called "second generation expert systems" (2nd GES). How do the motivations and results of this research relate to building tools for the workplace today? We provide an historical review of how the theory of expertise has developed, a progress report on a tool for designing and implementing model-based automation (Brahms), and a concrete example how we apply 2nd GES concepts today in an agent-based system for space flight operations (OCAMS). Brahms incorporates an ontology for modeling work practices, what people are doing in the course of a day, characterized as "activities." OCAMS was developed using a simulation-to-implementation methodology, in which a prototype tool was embedded in a simulation of future work practices. OCAMS uses model-based methods to interactively plan its actions and keep track of the work to be done. The problem solving methods of practice are interactive, employing reasoning for and through action in the real world. Analogously, it is as if a medical expert system were charged not just with interpreting culture results, but actually interacting with a patient. Our perspective shifts from building a "problem solving" (expert) system to building an actor in the world. The reusable components in work system designs include entire "problem solvers" (e.g., a planning subsystem), interoperability frameworks, and workflow agents that use and revise models dynamically in a network of people and tools. Consequently, the research focus shifts so "problem solving methods" include ways of knowing that models do not fit the world, and ways of interacting with other agents and people to gain or verify information and (ultimately) adapt rules and procedures to resolve problematic situations.

Expert system validation in prolog

NASA Technical Reports Server (NTRS)

Stock, Todd; Stachowitz, Rolf; Chang, Chin-Liang; Combs, Jacqueline

1988-01-01

An overview of the Expert System Validation Assistant (EVA) is being implemented in Prolog at the Lockheed AI Center. Prolog was chosen to facilitate rapid prototyping of the structure and logic checkers and since February 1987, we have implemented code to check for irrelevance, subsumption, duplication, deadends, unreachability, and cycles. The architecture chosen is extremely flexible and expansible, yet concise and complementary with the normal interactive style of Prolog. The foundation of the system is in the connection graph representation. Rules and facts are modeled as nodes in the graph and arcs indicate common patterns between rules. The basic activity of the validation system is then a traversal of the connection graph, searching for various patterns the system recognizes as erroneous. To aid in specifying these patterns, a metalanguage is developed, providing the user with the basic facilities required to reason about the expert system. Using the metalanguage, the user can, for example, give the Prolog inference engine the goal of finding inconsistent conclusions among the rules, and Prolog will search the graph intantiations which can match the definition of inconsistency. Examples of code for some of the checkers are provided and the algorithms explained. Technical highlights include automatic construction of a connection graph, demonstration of the use of metalanguage, the A* algorithm modified to detect all unique cycles, general-purpose stacks in Prolog, and a general-purpose database browser with pattern completion.

Development of a semi-autonomous service robot with telerobotic capabilities

NASA Technical Reports Server (NTRS)

Jones, J. E.; White, D. R.

1987-01-01

The importance to the United States of semi-autonomous systems for application to a large number of manufacturing and service processes is very clear. Two principal reasons emerge as the primary driving forces for development of such systems: enhanced national productivity and operation in environments whch are hazardous to humans. Completely autonomous systems may not currently be economically feasible. However, autonomous systems that operate in a limited operation domain or that are supervised by humans are within the technology capability of this decade and will likely provide reasonable return on investment. The two research and development efforts of autonomy and telerobotics are distinctly different, yet interconnected. The first addresses the communication of an intelligent electronic system with a robot while the second requires human communication and ergonomic consideration. Discussed here are work in robotic control, human/robot team implementation, expert system robot operation, and sensor development by the American Welding Institute, MTS Systems Corporation, and the Colorado School of Mines--Center for Welding Research.

Faultfinder: A diagnostic expert system with graceful degradation for onboard aircraft applications

NASA Technical Reports Server (NTRS)

Abbott, Kathy H.; Schutte, Paul C.; Palmer, Michael T.; Ricks, Wendell R.

1988-01-01

A research effort was conducted to explore the application of artificial intelligence technology to automation of fault monitoring and diagnosis as an aid to the flight crew. Human diagnostic reasoning was analyzed and actual accident and incident cases were reconstructed. Based on this analysis and reconstruction, diagnostic concepts were conceived and implemented for an aircraft's engine and hydraulic subsystems. These concepts are embedded within a multistage approach to diagnosis that reasons about time-based, causal, and qualitative information, and enables a certain amount of graceful degradation. The diagnostic concepts are implemented in a computer program called Faultfinder that serves as a research prototype.

Current Status and Future Trends of Diversity Initiatives in the Workplace: Diversity Experts' Perspective.

ERIC Educational Resources Information Center

Wentling, Rose Mary; Palma-Rivas, Nilda

1998-01-01

In-depth interviews with 12 diversity experts identified organizational and individual barriers inhibiting development of a diverse workforce. Primary reasons for diversity initiatives included improving productivity, enhancing social responsibility, and addressing legal concerns. (SK)

Towards a General Scientific Reasoning Engine.

ERIC Educational Resources Information Center

Carbonell, Jaime G.; And Others

Expert reasoning in the natural sciences appears to make extensive use of a relatively small number of general principles and reasoning strategies, each associated with a larger number of more specific inference patterns. Using a dual declarative hierarchy to represent strategic and factual knowledge, a framework for a robust scientific reasoning…

Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavez, Gregory M; Key, Brian P; Zerkle, David K

2009-01-01

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which canmore » be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.« less

A sustainable city environment through child safety and mobility-a challenge based on ITS?

PubMed

Leden, Lars; Gårder, Per; Schirokoff, Anna; Monterde-i-Bort, Hector; Johansson, Charlotta; Basbas, Socrates

2014-01-01

Our cities should be designed to accommodate everybody, including children. We will not move toward a more sustainable society unless we accept that children are people with transportation needs, and 'bussing' them around, or providing parental limousine services at all times, will not lead to sustainability. Rather, we will need to make our cities walkable for children, at least those above a certain age. Safety has two main aspects, traffic safety and personal safety (risk of assault). Besides being safe, children will also need an urban environment with reasonable mobility, where they themselves can reach destinations with reasonable effort; else they will still need to be driven. This paper presents the results of two expert questionnaires focusing on the potential safety and mobility benefits to child pedestrians of targeted types of intelligent transportation systems (ITS). Five different types of functional requests for children were identified based on previous work. The first expert questionnaire was structured to collect expert opinions on which ITS solutions or devices would be, and why, the most relevant ones to satisfy the five different functional requests of child pedestrians. Based on the first questionnaire, fifteen problem areas were defined. In the second questionnaire, the experts ranked the fifteen areas, and prioritized related ITS services, according to their potential for developing ITS services beneficial to children. Several ITS systems for improving pedestrian quality are discussed. ITS services can be used when a pedestrian route takes them to a dangerous street, dangerous crossing point or through a dangerous neighborhood. An improvement of safety and other qualities would lead to increased mobility and a more sustainable way of living. Children would learn how to live to support their own health and a sustainable city environment. But it will be up to national, regional and local governments, through their ministries and agencies and public works departments, to promote, fund, and possibly mandate such systems. It is clear that we need to offer an acceptable level of convenience, efficiency, comfort, safety and security to pedestrians but it is less clear if society will prioritize resources toward this. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-Bayesian Optical Inference Machines

NASA Astrophysics Data System (ADS)

Kadar, Ivan; Eichmann, George

1987-01-01

In a recent paper, Eichmann and Caulfield) presented a preliminary exposition of optical learning machines suited for use in expert systems. In this paper, we extend the previous ideas by introducing learning as a means of reinforcement by information gathering and reasoning with uncertainty in a non-Bayesian framework2. More specifically, the non-Bayesian approach allows the representation of total ignorance (not knowing) as opposed to assuming equally likely prior distributions.

The Next Wave. Volume 19, Number 2

DTIC Science & Technology

2012-01-01

Afghanistan and other war zones/These are but two examples of what have become almost routine reports of failures in system security. Increasingly...and to describe what it might look like. Academic and industry experts from a broad set of disciplines including security, economics, human factors...Dusko Pavlovic from Oxford University provides a unique and unexpected model for security to reason about what a security science might be. Anupam

Using the ICF to clarify team roles and demonstrate clinical reasoning in stroke rehabilitation.

PubMed

Tempest, Stephanie; McIntyre, Anne

2006-05-30

The International Classification of Functioning, Disability and Health (ICF) is advocated as a tool to structure rehabilitation and a universal language to aid communication, within the multi-disciplinary team (MDT). The ICF may also facilitate clarification of team roles and clinical reasoning for intervention. This article aims to explore both factors in stroke rehabilitation. Following a review of the literature, a summary was presented and discussed with clinicians working within stroke rehabilitation, to gather expert opinions. The discussions were informal, being part of service development and on-going education. The clinicians summarised key themes for the potential use of the ICF within clinical practice. Two key themes emerged from the literature and expert opinion for the potential use of the ICF in stroke rehabilitation: (i) to aid communication and structure service provision, (ii) to clarify team roles and aid clinical reasoning. Expert opinion was that clarification of team roles needs to occur at a local level due to the skill mix, particular interests, setting and staffing levels within individual teams. The ICF has the potential to demonstrate/facilitate clinical reasoning, especially when different MDT members are working on the same intervention. There is potential for the ICF to be used to clarify team roles and demonstrate clinical reasoning within stroke rehabilitation. Further experiential research is required to substantiate this view.

Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

PubMed

Du, Yuanwei; Guo, Yubin

2015-01-01

The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

Defining 'reasonable medical certainty' in court: What does it mean to medical experts in child abuse cases?

PubMed

Dias, Mark S; Boehmer, Susan; Johnston-Walsh, Lucy; Levi, Benjamin H

2015-12-01

Physicians and others who provide expert testimony in court cases involving alleged child abuse may be instructed to state their conclusions within a 'reasonable medical certainty' (RMC). However, neither judges nor jurors knows what degree of probability constitutes RMC for a given expert, nor whether different experts use different standards to formulate their opinions. We sought to better understand how experts define RMC in the context of court cases. An email survey was sent to members of six list-serves, representing four specialties, whose members testify in child abuse cases. Respondents were asked to define how RMC corresponded to (1) the numerical probability that abuse occurred, (2) the ordinal probability, and (3) how their determinations relate to common legal standards ('preponderance of the evidence', 'clear and convincing', and 'beyond a reasonable doubt'). Participants were also asked how comfortable they were in defining RMC; whether their definition changed according to the charges or type of proceeding; and how they would apply RMC to several hypothetical cases. The 294 list-serve participants who responded included child abuse pediatricians (46%), forensic pathologists (21%), pediatric neurosurgeons (15%), pediatric ophthalmologists (12%), and others (6%). Though 95% of respondents had testified in court, only 45% had received training in the definition of RMC. Only 37% were comfortable defining RMC. Although many responses were highly clustered and paired comparisons showed that 95% of participants' responses were internally consistent, there was variability in respondents' definitions of RMC. There is some variability in how child abuse expert witnesses define and use the term RMC; we provide suggestions about how to more accurately and transparently define RMC to ensure justice in these cases. Copyright © 2015 Elsevier Ltd. All rights reserved.

A clinical decision support system prototype for cardiovascular intensive care.

PubMed

Lau, F

1994-08-01

This paper describes the development and validation of a decision-support system prototype that can help manage hypovolemic hypotension in the Cardiovascular Intensive Care Unit (CVICU). The prototype uses physiologic pattern-matching, therapeutic protocols, computational drug-dosage response modeling and expert reasoning heuristics in its selection of intervention strategies and choices. As part of model testing, the prototype simulated real-time operation by processing historical physiologic and intervention data on a patient sequentially, generating alerts on questionable data, critiques of interventions instituted and recommendations on preferred interventions. Bench-testing with 399 interventions from 13 historical cases showed therapies for bleeding and fluid replacement proposed by the prototype were significantly more consistent (p < 0.0001) than those instituted by the staff when compared against expert critiques (80% versus 44%). This study has demonstrated the feasibility of formalizing hemodynamic management of CVICU patients in a manner that may be implemented and evaluated in a clinical setting.

An evaluation of a real-time fault diagnosis expert system for aircraft applications

NASA Technical Reports Server (NTRS)

Schutte, Paul C.; Abbott, Kathy H.; Palmer, Michael T.; Ricks, Wendell R.

1987-01-01

A fault monitoring and diagnosis expert system called Faultfinder was conceived and developed to detect and diagnose in-flight failures in an aircraft. Faultfinder is an automated intelligent aid whose purpose is to assist the flight crew in fault monitoring, fault diagnosis, and recovery planning. The present implementation of this concept performs monitoring and diagnosis for a generic aircraft's propulsion and hydraulic subsystems. This implementation is capable of detecting and diagnosing failures of known and unknown (i.e., unforseeable) type in a real-time environment. Faultfinder uses both rule-based and model-based reasoning strategies which operate on causal, temporal, and qualitative information. A preliminary evaluation is made of the diagnostic concepts implemented in Faultfinder. The evaluation used actual aircraft accident and incident cases which were simulated to assess the effectiveness of Faultfinder in detecting and diagnosing failures. Results of this evaluation, together with the description of the current Faultfinder implementation, are presented.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

PubMed

Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional reasoning in diagnostic problem solving

NASA Technical Reports Server (NTRS)

Sticklen, Jon; Bond, W. E.; Stclair, D. C.

1988-01-01

This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.

Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

NASA Astrophysics Data System (ADS)

Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

2018-05-01

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

Object-oriented model-driven control

NASA Technical Reports Server (NTRS)

Drysdale, A.; Mcroberts, M.; Sager, J.; Wheeler, R.

1994-01-01

A monitoring and control subsystem architecture has been developed that capitalizes on the use of modeldriven monitoring and predictive control, knowledge-based data representation, and artificial reasoning in an operator support mode. We have developed an object-oriented model of a Controlled Ecological Life Support System (CELSS). The model based on the NASA Kennedy Space Center CELSS breadboard data, tracks carbon, hydrogen, and oxygen, carbodioxide, and water. It estimates and tracks resorce-related parameters such as mass, energy, and manpower measurements such as growing area required for balance. We are developing an interface with the breadboard systems that is compatible with artificial reasoning. Initial work is being done on use of expert systems and user interface development. This paper presents an approach to defining universally applicable CELSS monitor and control issues, and implementing appropriate monitor and control capability for a particular instance: the KSC CELSS Breadboard Facility.

System perspectives of experts and farmers regarding the role of livelihood assets in risk perception: results from the structured mental model approach.

PubMed

Schoell, Regina; Binder, Claudia R

2009-02-01

Pesticide application is increasing and despite extensive educational programs farmers continue to take high health and environmental risks when applying pesticides. The structured mental model approach (SMMA) is a new method for risk perception analysis. It embeds farmers' risk perception into their livelihood system in the elaboration of a mental model (MM). Results from its first application are presented here. The study region is Vereda la Hoya (Colombia), an area characterized by subsistence farming, high use of pesticides, and a high incidence of health problems. Our hypothesis was that subsistence farmers were constrained by economic, environmental, and sociocultural factors, which consequently should influence their mental models. Thirteen experts and 10 farmers were interviewed and their MMs of the extended pesticide system elicited. The interviews were open-ended with the questions structured in three parts: (i) definition and ranking of types of capital with respect to their importance for the sustainability of farmers' livelihood; (ii) understanding the system and its dynamics; and (iii) importance of the agents in the farmers' agent network. Following this structure, each part of the interview was analyzed qualitatively and statistically. Our analyses showed that the mental models of farmers and experts differed significantly from each other. By applying the SMMA, we were also able to identify reasons for the divergence of experts' and farmers' MMs. Of major importance are the following factors: (i) culture and tradition; (ii) trust in the source of information; and (iii) feedback on knowledge.

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Visual analytics for aviation safety: A collaborative approach to sensemaking

NASA Astrophysics Data System (ADS)

Wade, Andrew

Visual analytics, the "science of analytical reasoning facilitated by interactive visual interfaces", is more than just visualization. Understanding the human reasoning process is essential for designing effective visualization tools and providing correct analyses. This thesis describes the evolution, application and evaluation of a new method for studying analytical reasoning that we have labeled paired analysis. Paired analysis combines subject matter experts (SMEs) and tool experts (TE) in an analytic dyad, here used to investigate aircraft maintenance and safety data. The method was developed and evaluated using interviews, pilot studies and analytic sessions during an internship at the Boeing Company. By enabling a collaborative approach to sensemaking that can be captured by researchers, paired analysis yielded rich data on human analytical reasoning that can be used to support analytic tool development and analyst training. Keywords: visual analytics, paired analysis, sensemaking, boeing, collaborative analysis.

Autonomous satellite command and control: A comparison with other military systems

NASA Technical Reports Server (NTRS)

Kruchten, Robert J.; Todd, Wayne

1988-01-01

Existing satellite concepts of operation depend on readily available experts and are extremely manpower intensive. Areas of expertise required include mission planning, mission data interpretation, telemetry monitoring, and anomaly resolution. The concepts of operation have envolved to their current state in part because space systems have tended to be treated more as research and development assets rather than as operational assets. These methods of satellite command and control will be inadequate in the future because of the availability, survivability, and capability of human experts. Because space systems have extremely high reliability and limited access, they offer challenges not found in other military systems. Thus, automation techniques used elsewhere are not necessarily applicable to space systems. A program to make satellites much more autonomous has been developed, using a variety of advanced software techniques. The problem the program is addressing, some possible solutions, the goals of the Rome Air Development Center (RADC) program, the rationale as to why the goals are reasonable, and the current program status are discussed. Also presented are some of the concepts used in the program and how they differ from more traditional approaches.

Analysis of underlying causes of inter-expert disagreement in retinopathy of prematurity diagnosis. Application of machine learning principles.

PubMed

Ataer-Cansizoglu, E; Kalpathy-Cramer, J; You, S; Keck, K; Erdogmus, D; Chiang, M F

2015-01-01

Inter-expert variability in image-based clinical diagnosis has been demonstrated in many diseases including retinopathy of prematurity (ROP), which is a disease affecting low birth weight infants and is a major cause of childhood blindness. In order to better understand the underlying causes of variability among experts, we propose a method to quantify the variability of expert decisions and analyze the relationship between expert diagnoses and features computed from the images. Identification of these features is relevant for development of computer-based decision support systems and educational systems in ROP, and these methods may be applicable to other diseases where inter-expert variability is observed. The experiments were carried out on a dataset of 34 retinal images, each with diagnoses provided independently by 22 experts. Analysis was performed using concepts of Mutual Information (MI) and Kernel Density Estimation. A large set of structural features (a total of 66) were extracted from retinal images. Feature selection was utilized to identify the most important features that correlated to actual clinical decisions by the 22 study experts. The best three features for each observer were selected by an exhaustive search on all possible feature subsets and considering joint MI as a relevance criterion. We also compared our results with the results of Cohen's Kappa [36] as an inter-rater reliability measure. The results demonstrate that a group of observers (17 among 22) decide consistently with each other. Mean and second central moment of arteriolar tortuosity is among the reasons of disagreement between this group and the rest of the observers, meaning that the group of experts consider amount of tortuosity as well as the variation of tortuosity in the image. Given a set of image-based features, the proposed analysis method can identify critical image-based features that lead to expert agreement and disagreement in diagnosis of ROP. Although tree-based features and various statistics such as central moment are not popular in the literature, our results suggest that they are important for diagnosis.

The Science of Computing: Expert Systems

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1986-01-01

The creative urge of human beings is coupled with tremendous reverence for logic. The idea that the ability to reason logically--to be rational--is closely tied to intelligence was clear in the writings of Plato. The search for greater understanding of human intelligence led to the development of mathematical logic, the study of methods of proving the truth of statements by manipulating the symbols in which they are written without regard to the meanings of those symbols. By the nineteenth century a search was under way for a universal system of logic, one capable of proving anything provable in any other system.

METEOR - an artificial intelligence system for convective storm forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elio, R.; De haan, J.; Strong, G.S.

1987-03-01

An AI system called METEOR, which uses the meteorologist's heuristics, strategies, and statistical tools to forecast severe hailstorms in Alberta, is described, emphasizing the information and knowledge that METEOR uses to mimic the forecasting procedure of an expert meteorologist. METEOR is then discussed as an AI system, emphasizing the ways in which it is qualitatively different from algorithmic or statistical approaches to prediction. Some features of METEOR's design and the AI techniques for representing meteorological knowledge and for reasoning and inference are presented. Finally, some observations on designing and implementing intelligent consultants for meteorological applications are made. 7 references.

The impact of two multiple-choice question formats on the problem-solving strategies used by novices and experts.

PubMed

Coderre, Sylvain P; Harasym, Peter; Mandin, Henry; Fick, Gordon

2004-11-05

Pencil-and-paper examination formats, and specifically the standard, five-option multiple-choice question, have often been questioned as a means for assessing higher-order clinical reasoning or problem solving. This study firstly investigated whether two paper formats with differing number of alternatives (standard five-option and extended-matching questions) can test problem-solving abilities. Secondly, the impact of the alternatives number on psychometrics and problem-solving strategies was examined. Think-aloud protocols were collected to determine the problem-solving strategy used by experts and non-experts in answering Gastroenterology questions, across the two pencil-and-paper formats. The two formats demonstrated equal ability in testing problem-solving abilities, while the number of alternatives did not significantly impact psychometrics or problem-solving strategies utilized. These results support the notion that well-constructed multiple-choice questions can in fact test higher order clinical reasoning. Furthermore, it can be concluded that in testing clinical reasoning, the question stem, or content, remains more important than the number of alternatives.

Development and Validation of a Tool to Evaluate the Evolution of Clinical Reasoning in Trauma Using Virtual Patients.

PubMed

Fleiszer, David; Hoover, Michael L; Posel, Nancy; Razek, Tarek; Bergman, Simon

Undergraduate medical students at a large academic trauma center are required to manage a series of online virtual trauma patients as a mandatory exercise during their surgical rotation. Clinical reasoning during undergraduate medical education can be difficult to assess. The purpose of the study was to determine whether we could use components of the students' virtual patient management to measure changes in their clinical reasoning over the course of the clerkship year. In order to accomplish this, we decided to determine if the use of scoring rubrics could change the traditional subjective assessment to a more objective evaluation. Two groups of students, one at the beginning of clerkship (Juniors) and one at the end of clerkship (Seniors), were chosen. Each group was given the same virtual patient case, a clinical scenario based on the Advanced Trauma Life Support (ATLS) Primary Trauma Survey, which had to be completed during their trauma rotation. The learner was required to make several key patient management choices based on their clinical reasoning, which would take them along different routes through the case. At the end of the case they had to create a summary report akin to sign-off. These summaries were graded independently by two domain "Experts" using a traditional subjective surgical approach to assessment and by two "Non-Experts" using two internally validated scoring rubrics. One rubric assessed procedural or domain knowledge (Procedural Rubric), while the other rubric highlighted semantic qualifiers (Semantic Rubric). Each of the rubrics was designed to reflect established components of clinical reasoning. Student's t-tests were used to compare the rubric scores for the two groups and Cohen's d was used to determine effect size. Kendall's τ was used to compare the difference between the two groups based on the "Expert's" subjective assessment. Inter-rater reliability (IRR) was determined using Cronbach's alpha. The Seniors did better than the Juniors with respect to "Procedural" issues but not for "Semantic" issues using the rubrics as assessed by the "Non-Experts". The average Procedural rubric score for the Senior group was 59% ± 13% while for the junior group, it was 51% ± 12% (t (80) = 2.715; p = 0.008; Cohen's d = 1.53). The average Semantic rubric score for the Senior group was 31% ± 15% while for the Junior group, it was 28% ± 14% (t (80) = 1.010; p = .316, ns). There was no statistical difference in the marks given to the Senior versus Junior groups by the "Experts" (Kendall's τ = 0.182, p = 0.07). The IRR between the "Non-Experts" using the rubrics was higher than the IRR of the "Experts" using the traditional surgical approach to assessment. The Cronbach's alpha for the Procedural and Semantic rubrics was 0.94 and 0.97, respectively, indicating very high IRR. The correlation between the Procedural rubric scores and "Experts" assessment was approximately r = 0.78, and that between the Semantic rubric and the "Experts" assessment was roughly r = 0.66, indicating high concurrent validity for the Procedural rubric and moderately high validity for the Semantic rubric. Clinical reasoning, as measured by some of its "procedural" features, improves over the course of the clerkship year. Rubrics can be created to objectively assess the summary statement of an online interactive trauma VP for "procedural" issues but not for "semantic" issues. Using IRR as a measure, the quality of assessment is improved using the rubrics. The "Procedural" rubric appears to measure changes in clinical reasoning over the course of 3rd-year undergraduate clinical studies. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Knowledge and intelligent computing system in medicine.

PubMed

Pandey, Babita; Mishra, R B

2009-03-01

Knowledge-based systems (KBS) and intelligent computing systems have been used in the medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) whereas intelligent computing method (ICM) encompasses genetic algorithm (GA), artificial neural network (ANN), fuzzy logic (FL) and others. The combination of methods in KBS such as CBR-RBR, CBR-MBR and RBR-CBR-MBR and the combination of methods in ICM is ANN-GA, fuzzy-ANN, fuzzy-GA and fuzzy-ANN-GA. The combination of methods from KBS to ICM is RBR-ANN, CBR-ANN, RBR-CBR-ANN, fuzzy-RBR, fuzzy-CBR and fuzzy-CBR-ANN. In this paper, we have made a study of different singular and combined methods (185 in number) applicable to medical domain from mid 1970s to 2008. The study is presented in tabular form, showing the methods and its salient features, processes and application areas in medical domain (diagnosis, treatment and planning). It is observed that most of the methods are used in medical diagnosis very few are used for planning and moderate number in treatment. The study and its presentation in this context would be helpful for novice researchers in the area of medical expert system.

Solutions to time variant problems of real-time expert systems

NASA Technical Reports Server (NTRS)

Yeh, Show-Way; Wu, Chuan-Lin; Hung, Chaw-Kwei

1988-01-01

Real-time expert systems for monitoring and control are driven by input data which changes with time. One of the subtle problems of this field is the propagation of time variant problems from rule to rule. This propagation problem is even complicated under a multiprogramming environment where the expert system may issue test commands to the system to get data and to access time consuming devices to retrieve data for concurrent reasoning. Two approaches are used to handle the flood of input data. Snapshots can be taken to freeze the system from time to time. The expert system treats the system as a stationary one and traces changes by comparing consecutive snapshots. In the other approach, when an input is available, the rules associated with it are evaluated. For both approaches, if the premise condition of a fired rule is changed to being false, the downstream rules should be deactivated. If the status change is due to disappearance of a transient problem, actions taken by the fired downstream rules which are no longer true may need to be undone. If a downstream rule is being evaluated, it should not be fired. Three mechanisms for solving this problem are discussed: tracing, backward checking, and censor setting. In the forward tracing mechanism, when the premise conditions of a fired rule become false, the premise conditions of downstream rules which have been fired or are being evaluated due to the firing of that rule are reevaluated. A tree with its root at the rule being deactivated is traversed. In the backward checking mechanism, when a rule is being fired, the expert system checks back on the premise conditions of the upstream rules that result in evaluation of the rule to see whether it should be fired. The root of the tree being traversed is the rule being fired. In the censor setting mechanism, when a rule is to be evaluated, a censor is constructed based on the premise conditions of the upstream rules and the censor is evaluated just before the rule is fired. Unlike the backward checking mechanism, this one does not search the upstream rules. This paper explores the details of implementation of the three mechanisms.

Expert clinical reasoning and pain assessment in mechanically ventilated patients: A descriptive study.

PubMed

Gerber, Anne; Thevoz, Anne-Laure; Ramelet, Anne-Sylvie

2015-02-01

Pain assessment in mechanically ventilated patients is challenging, because nurses need to decode pain behaviour, interpret pain scores, and make appropriate decisions. This clinical reasoning process is inherent to advanced nursing practice, but is poorly understood. A better understanding of this process could contribute to improved pain assessment and management. This study aimed to describe the indicators that influence expert nurses' clinical reasoning when assessing pain in critically ill nonverbal patients. This descriptive observational study was conducted in the adult intensive care unit (ICU) of a tertiary referral hospital in Western Switzerland. A purposive sample of expert nurses, caring for nonverbal ventilated patients who received sedation and analgesia, were invited to participate in the study. Data were collected in "real life" using recorded think-aloud combined with direct non-participant observation and brief interviews. Data were analysed using deductive and inductive content analyses using a theoretical framework related to clinical reasoning and pain. Seven expert nurses with an average of 7.85 (±3.1) years of critical care experience participated in the study. The patients had respiratory distress (n=2), cardiac arrest (n=2), sub-arachnoid bleeding (n=1), and multi-trauma (n=2). A total of 1344 quotes in five categories were identified. Patients' physiological stability was the principal indicator for making decision in relation to pain management. Results also showed that it is a permanent challenge for nurses to discriminate situations requiring sedation from situations requiring analgesia. Expert nurses mainly used working knowledge and patterns to anticipate and prevent pain. Patient's clinical condition is important for making decision about pain in critically ill nonverbal patients. The concept of pain cannot be assessed in isolation and its assessment should take the patient's clinical stability and sedation into account. Further research is warranted to confirm these results. Copyright © 2014. Published by Elsevier Ltd.

Intelligent monitoring of critical pathological events during anesthesia.

PubMed

Gohil, Bhupendra; Gholamhhosseini, Hamid; Harrison, Michael J; Lowe, Andrew; Al-Jumaily, Ahmed

2007-01-01

Expert algorithms in the field of intelligent patient monitoring have rapidly revolutionized patient care thereby improving patient safety. Patient monitoring during anesthesia requires cautious attention by anesthetists who are monitoring many modalities, diagnosing clinically critical events and performing patient management tasks simultaneously. The mishaps that occur during day-to-day anesthesia causing disastrous errors in anesthesia administration were classified and studied by Reason [1]. Human errors in anesthesia account for 82% of the preventable mishaps [2]. The aim of this paper is to develop a clinically useful diagnostic alarm system for detecting critical events during anesthesia administration. The development of an expert diagnostic alarm system called ;RT-SAAM' for detecting critical pathological events in the operating theatre is presented. This system provides decision support to the anesthetist by presenting the diagnostic results on an integrative, ergonomic display and thus enhancing patient safety. The performance of the system was validated through a series of offline and real-time testing in the operation theatre. When detecting absolute hypovolaemia (AHV), moderate level of agreement was observed between RT-SAAM and the human expert (anesthetist) during surgical procedures. RT-SAAM is a clinically useful diagnostic tool which can be easily modified for diagnosing additional critical pathological events like relative hypovolaemia, fall in cardiac output, sympathetic response and malignant hyperpyrexia during surgical procedures. RT-SAAM is currently being tested at the Auckland City Hospital with ethical approval from the local ethics committees.

Engine Data Interpretation System (EDIS)

NASA Technical Reports Server (NTRS)

Cost, Thomas L.; Hofmann, Martin O.

1990-01-01

A prototype of an expert system was developed which applies qualitative or model-based reasoning to the task of post-test analysis and diagnosis of data resulting from a rocket engine firing. A combined component-based and process theory approach is adopted as the basis for system modeling. Such an approach provides a framework for explaining both normal and deviant system behavior in terms of individual component functionality. The diagnosis function is applied to digitized sensor time-histories generated during engine firings. The generic system is applicable to any liquid rocket engine but was adapted specifically in this work to the Space Shuttle Main Engine (SSME). The system is applied to idealized data resulting from turbomachinery malfunction in the SSME.

Reconsidering Planning and Management of Medical Devices Procurement in Public Health Services in Cyprus.

PubMed

Theodorou, Mamas; Georgiou, Marina; Nikolentzos, Athanasios; Bellali, Thalia

2015-04-19

Hospital procurement is a crucial field for any health care system, not only for economic reasons but also for reasons related to the quality and safety of the services provided. That is why the process of procurement is, in most countries, governed by a strict legal framework and policy mechanisms. This study investigates the problems and inefficiencies associated with the procurement of medical devices in public hospitals in Cyprus and formulates empirically documented proposals for improvement. Using the Delphi method, a group of 38 experts approach the procurement system in Cyprus from different angles, achieving high rates of consensus on 35 different statements on the weaknesses and problems of the current medical device procurement system, as well as presenting proposals and recommendations for improvement. The findings are highly valuable for future policy initiatives in Cyprus in the light of the economic crisis and the expected implementation of the new General Health Insurance System (GeSY), which the Government of the Republic of Cyprus and the Troika has agreed.

AI and simulation: What can they learn from each other

NASA Technical Reports Server (NTRS)

Colombano, Silvano P.

1988-01-01

Simulation and Artificial Intelligence share a fertile common ground both from a practical and from a conceptual point of view. Strengths and weaknesses of both Knowledge Based System and Modeling and Simulation are examined and three types of systems that combine the strengths of both technologies are discussed. These types of systems are a practical starting point, however, the real strengths of both technologies will be exploited only when they are combined in a common knowledge representation paradigm. From an even deeper conceptual point of view, one might even argue that the ability to reason from a set of facts (i.e., Expert System) is less representative of human reasoning than the ability to make a model of the world, change it as required, and derive conclusions about the expected behavior of world entities. This is a fundamental problem in AI, and Modeling Theory can contribute to its solution. The application of Knowledge Engineering technology to a Distributed Processing Network Simulator (DPNS) is discussed.

[Description of the mental processes occurring during clinical reasoning].

PubMed

Pottier, P; Planchon, B

2011-06-01

Clinical reasoning is a highly complex system with multiple inter-dependent mental activities. Gaining a better understanding of those cognitive processes has two practical implications: for physicians, being able to analyse their own reasoning method may prove to be helpful in diagnostic dead end; for medical teachers, identifying problem-solving strategies used by medical students may foster an appropriate individual feed-back aiming at improving their clinical reasoning skills. On the basis of a detailed literature review, the main diagnostic strategies and their related pattern of mental processes are described and illustrated with a concrete example, going from the patient's complaint to the chosen solution. Inductive, abductive and deductive diagnostic approaches are detailed. Different strategies for collecting data (exhaustive or oriented) and for problem-building are described. The place of problem solving strategies such as pattern-recognition, scheme inductive process, using of clinical script, syndrome grouping and mental hypotheses test is considered. This work aims at breaking up mental activities in process within clinical reasoning reminding that expert reasoning is characterised by the ability to use and structure the whole of these activities in a coherent system, using combined strategies in order to guarantee a better accuracy of their diagnosis. Copyright © 2010 Société nationale française de médecine interne (SNFMI). Published by Elsevier SAS. All rights reserved.

A Review of Diagnostic Techniques for ISHM Applications

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Biswas, Gautam; Aaseng, Gordon; Narasimhan, Sriam; Pattipati, Krishna

2005-01-01

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Module generation for self-testing integrated systems

NASA Astrophysics Data System (ADS)

Vanriessen, Ronald Pieter

Hardware used for self test in VLSI (Very Large Scale Integrated) systems is reviewed, and an architecture to control the test hardware in an integrated system is presented. Because of the increase of test times, the use of self test techniques has become practically and economically viable for VLSI systems. Beside the reduction in test times and costs, self test also provides testing at operational speeds. Therefore, a suitable combination of scan path and macrospecific (self) tests is required to reduce test times and costs. An expert system that can be used in a silicon compilation environment is presented. The approach requires a minimum of testability knowledge from a system designer. A user friendly interface was described for specifying and modifying testability requirements by a testability expert. A reason directed backtracking mechanism is used to solve selection failures. Both the hierarchical testable architecture and the design for testability expert system are used in a self test compiler. The definition of a self test compiler was given. A self test compiler is a software tool that selects an appropriate test method for every macro in a design. The hardware to control a macro test will be included in the design automatically. As an example, the integration of the self-test compiler in a silicon compilation system PIRAMID was described. The design of a demonstrator circuit by self test compiler is described. This circuit consists of two self testable macros. Control of the self test hardware is carried out via the test access port of the boundary scan standard.

The United States of America and the People`s Republic of China experts report on integrated gasification combined-cycle technology (IGCC) (in English;Chinese)

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1996-12-01

A report written by the leading US and Chinese experts in Integrated Gasification Combined Cycle (IGCC) power plants, intended for high level decision makers, may greatly accelerate the development of an IGCC demonstration project in the People`s Republic of China (PRC). The potential market for IGCC systems in China and the competitiveness of IGCC technology with other clean coal options for China have been analyzed in the report. Such information will be useful not only to the Chinese government but also to US vendors and companies. The goal of this report is to analyze the energy supply structure of China,more » China`s energy and environmental protection demand, and the potential market in China in order to make a justified and reasonable assessment on feasibility of the transfer of US Clean Coal Technologies to China. The Expert Report was developed and written by the joint US/PRC IGCC experts and will be presented to the State Planning Commission (SPC) by the President of the CAS to ensure consideration of the importance of IGCC for future PRC power production.« less

Exploring how students think: a new method combining think-aloud and concept mapping protocols.

PubMed

Pottier, Pierre; Hardouin, Jean-Benoit; Hodges, Brian D; Pistorius, Marc-Antoine; Connault, Jérome; Durant, Cécile; Clairand, Renaud; Sebille, Véronique; Barrier, Jacques-Henri; Planchon, Bernard

2010-09-01

A key element of medical competence is problem solving. Previous work has shown that doctors use inductive reasoning to progress from facts to hypotheses and deductive reasoning to move from hypotheses to the gathering of confirmatory information. No individual assessment method has been designed to quantify the use of inductive and deductive procedures within clinical reasoning. The aim of this study was to explore the feasibility and reliability of a new method which allows for the rapid identification of the style (inductive or deductive) of clinical reasoning in medical students and experts. The study included four groups of four participants. These comprised groups of medical students in Years 3, 4 and 5 and a group of specialists in internal medicine, all at a medical school with a 6-year curriculum in France. Participants were asked to solve four clinical problems by thinking aloud. The thinking expressed aloud was immediately transcribed into concept maps by one or two 'writers' trained to distinguish inductive and deductive links. Reliability was assessed by estimating the inter-writer correlation. The calculated rate of inductive reasoning, the richness score and the rate of exhaustiveness of reasoning were compared according to the level of expertise of the individual and the type of clinical problem. The total number of maps drawn amounted to 32 for students in Year 4, 32 for students in Year 5, 16 for students in Year 3 and 16 for experts. A positive correlation was found between writers (R = 0.66-0.93). Richness scores and rates of exhaustiveness of reasoning did not differ according to expertise level. The rate of inductive reasoning varied as expected according to the nature of the clinical problem and was lower in experts (41% versus 67%). This new method showed good reliability and may be a promising tool for the assessment of medical problem-solving skills, giving teachers a means of diagnosing how their students think when they are confronted with clinical problems.

Treatment of severe psoriasis in children: recommendations of an Italian expert group.

PubMed

Fortina, Anna Belloni; Bardazzi, Federico; Berti, Samantha; Carnevale, Claudia; Di Lernia, Vito; El Hachem, Maya; Neri, Iria; Gelmetti, Carlo Mario; Lora, Viviana; Mazzatenta, Carlo; Milioto, Mirella; Moretta, Gaia; Patrizi, Annalisa; Peris, Ketty; Villani, Alberto

2017-10-01

This article provides comprehensive recommendations for the systemic treatment of severe pediatric psoriasis based on evidence obtained from a systematic review of the literature and the consensus opinion of expert dermatologists and pediatricians. For each systemic treatment, the grade of recommendation (A, B, C) based on the treatment's approval by the European Medicines Agency for childhood psoriasis and the experts' opinions is discussed. The grade of recommendation for narrow-band-ultraviolet B phototherapy, cyclosporine, and retinoids is C, while that for methotrexate is C/B. The use of adalimumab, etanercept, and ustekinumab has a grade A recommendation. No conventional systemic treatments are approved for pediatric psoriasis. Adalimumab is approved by the European Medicines Agency as a first-line treatment for severe chronic plaque psoriasis in children (≥ 4 years old) and adolescents. Etanercept and ustekinumab are approved as second-line therapy in children ≥ 6 and ≥ 12 years, respectively. A treatment algorithm as well as practical tools (i.e., tabular summaries of differential diagnoses, treatment mechanism of actions, dosing regimens, control parameters) are provided to assist in therapeutic reasoning and decision-making for individual patients. These treatment recommendations are endorsed by major Italian Pediatric and Dermatology Societies. What is Known: • Guidelines for the treatment of severe pediatric psoriasis are lacking and most traditional systemic treatments are not approved for use in young patients. Although there has been decades of experience with some of the traditional agents such as phototherapy, acitretin, and cyclosporine in children, there are no RCTs on their pediatric use while RCTs investigating new biologic agents have been performed. What is New: • In this manuscript, an Italian multidisciplinary team of experts focused on treatment recommendations for severe forms of psoriasis in children based on an up-to-date review of the literature and experts' opinions.

Teaching clinical reasoning by making thinking visible: an action research project with allied health clinical educators.

PubMed

Delany, Clare; Golding, Clinton

2014-01-30

Clinical reasoning is fundamental to all forms of professional health practice, however it is also difficult to teach and learn because it is complex, tacit, and effectively invisible for students. In this paper we present an approach for teaching clinical reasoning based on making expert thinking visible and accessible to students. Twenty-one experienced allied health clinical educators from three tertiary Australian hospitals attended up to seven action research discussion sessions, where they developed a tentative heuristic of their own clinical reasoning, trialled it with students, evaluated if it helped their students to reason clinically, and then refined it so the heuristic was targeted to developing each student's reasoning skills. Data included participants' written descriptions of the thinking routines they developed and trialed with their students and the transcribed action research discussion sessions. Content analysis was used to summarise this data and categorise themes about teaching and learning clinical reasoning. Two overriding themes emerged from participants' reports about using the 'making thinking visible approach'. The first was a specific focus by participating educators on students' understanding of the reasoning process and the second was heightened awareness of personal teaching styles and approaches to teaching clinical reasoning. We suggest that the making thinking visible approach has potential to assist educators to become more reflective about their clinical reasoning teaching and acts as a scaffold to assist them to articulate their own expert reasoning and for students to access and use.

Teaching clinical reasoning by making thinking visible: an action research project with allied health clinical educators

PubMed Central

2014-01-01

Background Clinical reasoning is fundamental to all forms of professional health practice, however it is also difficult to teach and learn because it is complex, tacit, and effectively invisible for students. In this paper we present an approach for teaching clinical reasoning based on making expert thinking visible and accessible to students. Methods Twenty-one experienced allied health clinical educators from three tertiary Australian hospitals attended up to seven action research discussion sessions, where they developed a tentative heuristic of their own clinical reasoning, trialled it with students, evaluated if it helped their students to reason clinically, and then refined it so the heuristic was targeted to developing each student’s reasoning skills. Data included participants’ written descriptions of the thinking routines they developed and trialed with their students and the transcribed action research discussion sessions. Content analysis was used to summarise this data and categorise themes about teaching and learning clinical reasoning. Results Two overriding themes emerged from participants’ reports about using the ‘making thinking visible approach’. The first was a specific focus by participating educators on students’ understanding of the reasoning process and the second was heightened awareness of personal teaching styles and approaches to teaching clinical reasoning. Conclusions We suggest that the making thinking visible approach has potential to assist educators to become more reflective about their clinical reasoning teaching and acts as a scaffold to assist them to articulate their own expert reasoning and for students to access and use. PMID:24479414

Murder, insanity, and medical expert witnesses.

PubMed

Ciccone, J R

1992-06-01

Recent advances in the ability to study brain anatomy and function and attempts to link these findings with human behavior have captured the attention of the legal system. This had led to the increasing use of the "neurological defense" to support a plea of not guilty by reason of insanity. This article explores the history of the insanity defense and explores the role of the medical expert witnesses in integrating clinical and laboratory findings, eg, computed tomographic scans, magnetic resonance scans, and single-photon emission computed tomographic scans. Three cases involving murder and brain dysfunction are discussed: the first case involves a subarachnoid hemorrhage resulting in visual perceptual and memory impairment; the second case, a diagnosis of Alzheimer's disease; and the third case, the controverted diagnosis of complex partial seizures in a serial killer.

Developing and Testing of a Software Prototype to Support Diagnostic Reasoning of Nursing Students.

PubMed

de Sousa, Vanessa Emille Carvalho; de Oliveira Lopes, Marcos Venícios; Keenan, Gail M; Lopez, Karen Dunn

2018-04-01

To design and test educational software to improve nursing students' diagnostic reasoning through NANDA-I-based clinical scenarios. A mixed method approach was used and included content validation by a panel of 13 experts and prototype testing by a sample of 56 students. Experts' suggestions included writing adjustments, new response options, and replacement of clinical information on the scenarios. Percentages of students' correct answers were 65.7%, 62.2%, and 60.5% for related factors, defining characteristics, and nursing diagnoses, respectively. Full development of this software shows strong potential for enhancing students' diagnostic reasoning. New graduates may be able to apply diagnostic reasoning more rapidly by exercising their diagnostic skills within this software. Desenvolver e testar um protótipo de software educativo para melhorar o raciocínio diagnóstico de estudantes de enfermagem. MÉTODOS: Uma abordagem mista foi utilizada e incluiu validação de conteúdo por 13 experts e testagem do protótipo por 56 estudantes. Sugestões dos experts incluíram ajustes na escrita, inclusão de novas opções de resposta e substituição de dados clínicos nos cenários. Os percentuais de respostas corretas dos estudantes foram 65,7%, 62,2% e 60,5% para fatores relacionados, características definidoras e diagnósticos de enfermagem respectivamente. CONCLUSÃO: O desenvolvimento deste software tem um forte potencial para melhorar o raciocínio diagnóstico de estudantes. IMPLICAÇÕES PARA A PRÁTICA EM ENFERMAGEM: Através deste software, enfermeiros poderão ser capazes de exercitar o raciocínio diagnóstico e aplicá-lo mais rapidamente. © 2016 NANDA International, Inc.

Automated simulation as part of a design workstation

NASA Technical Reports Server (NTRS)

Cantwell, E.; Shenk, T.; Robinson, P.; Upadhye, R.

1990-01-01

A development project for a design workstation for advanced life-support systems incorporating qualitative simulation, required the implementation of a useful qualitative simulation capability and the integration of qualitative and quantitative simulations, such that simulation capabilities are maximized without duplication. The reason is that to produce design solutions to a system goal, the behavior of the system in both a steady and perturbed state must be represented. The paper reports on the Qualitative Simulation Tool (QST), on an expert-system-like model building and simulation interface toll called ScratchPad (SP), and on the integration of QST and SP with more conventional, commercially available simulation packages now being applied in the evaluation of life-support system processes and components.

Do Reading Experts Agree with MCAT Verbal Reasoning Item Classifications?

ERIC Educational Resources Information Center

Jackson, Evelyn W.; And Others

1994-01-01

Examined whether expert raters (n=5) could agree about classification of Medical College Admission Test (MCAT) items and whether they agreed with MCAT student manual in labeling skill being measured by each test item. Results revealed difficulties in replicating authors' labeling of skills for reading items on practice test provided with 1991 MCAT…

Expert-Novice Differences in Memory, Abstraction, and Reasoning in the Domain of Literature.

ERIC Educational Resources Information Center

Zeitz, Colleen M.

1994-01-01

Explored the information processing abilities associated with expertise in literature in high school and college students. Found that literary experts were superior to novices in gist-level recall, extraction of interpretations, and breadth of aspects addressed of literary texts but not in comprehension of scientific texts. (AA)

Improving Students' Intrinsic Motivation in Piano Learning: Expert Teacher Voices

ERIC Educational Resources Information Center

Cheng, Zijia; Southcott, Jane

2016-01-01

Many students learn to play the piano but some lack the motivation to continue learning. Many students learn for extrinsic reasons. This research will explore understandings about student motivation held by expert piano teachers who have developed strategies to improve their students' intrinsic motivation to begin and continue learning. This small…

Intuition: Two Caregivers' Descriptions of How They Provide Severely Demented Patients with Loving Care.

ERIC Educational Resources Information Center

Hellner, Britt Mari; Norberg, Astrid

1994-01-01

Interviewed two expert caregivers about their experiences of caring for severely demented patients. Ethical reasoning, exemplified by tender descriptions of relatedness to patients, indicated that expert caregivers used sound knowledge combined with imagination, empathy, and intuition to grasp situation, where patient is regarded as person with…

Improving Automated Endmember Identification for Linear Unmixing of HyspIRI Spectral Data.

NASA Astrophysics Data System (ADS)

Gader, P.

2016-12-01

The size of data sets produced by imaging spectrometers is increasing rapidly. There is already a processing bottleneck. Part of the reason for this bottleneck is the need for expert input using interactive software tools. This process can be very time consuming and laborious but is currently crucial to ensuring the quality of the analysis. Automated algorithms can mitigate this problem. Although it is unlikely that processing systems can become completely automated, there is an urgent need to increase the level of automation. Spectral unmixing is a key component to processing HyspIRI data. Algorithms such as MESMA have been demonstrated to achieve results but require carefully, expert construction of endmember libraries. Unfortunately, many endmembers found by automated algorithms for finding endmembers are deemed unsuitable by experts because they are not physically reasonable. Unfortunately, endmembers that are not physically reasonable can achieve very low errors between the linear mixing model with those endmembers and the original data. Therefore, this error is not a reasonable way to resolve the problem on "non-physical" endmembers. There are many potential approaches for resolving these issues, including using Bayesian priors, but very little attention has been given to this problem. The study reported on here considers a modification of the Sparsity Promoting Iterated Constrained Endmember (SPICE) algorithm. SPICE finds endmembers and abundances and estimates the number of endmembers. The SPICE algorithm seeks to minimize a quadratic objective function with respect to endmembers E and fractions P. The modified SPICE algorithm, which we refer to as SPICED, is obtained by adding the term D to the objective function. The term D pressures the algorithm to minimize sum of the squared differences between each endmember and a weighted sum of the data. By appropriately modifying the, the endmembers are pushed towards a subset of the data with the potential for becoming exactly equal to the data points. The algorithm has been applied to spectral data and the differences between the endmembers resulting from ecorded. The results so far are that the endmembers found SPICED are approximately 25% closer to the data with indistinguishable reconstruction error compared to those found using SPICE.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)

PubMed Central

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497

Development of an expert system for the simulation model for casting metal substructure of a metal-ceramic crown design.

PubMed

Matin, Ivan; Hadzistevic, Miodrag; Vukelic, Djordje; Potran, Michal; Brajlih, Tomaz

2017-07-01

Nowadays, the integrated CAD/CAE systems are favored solutions for the design of simulation models for casting metal substructures of metal-ceramic crowns. The worldwide authors have used different approaches to solve the problems using an expert system. Despite substantial research progress in the design of experts systems for the simulation model design and manufacturing have insufficiently considered the specifics of casting in dentistry, especially the need for further CAD, RE, CAE for the estimation of casting parameters and the control of the casting machine. The novel expert system performs the following: CAD modeling of the simulation model for casting, fast modeling of gate design, CAD eligibility and cast ability check of the model, estimation and running of the program code for the casting machine, as well as manufacturing time reduction of the metal substructure. The authors propose an integration method using common data model approach, blackboard architecture, rule-based reasoning and iterative redesign method. Arithmetic mean roughness values was determinated with constant Gauss low-pass filter (cut-off length of 2.5mm) according to ISO 4287 using Mahr MARSURF PS1. Dimensional deviation between the designed model and manufactured cast was determined using the coordinate measuring machine Zeiss Contura G2 and GOM Inspect software. The ES allows for obtaining the castings derived roughness grade number N7. The dimensional deviation between the simulation model of the metal substructure and the manufactured cast is 0.018mm. The arithmetic mean roughness values measured on the casting substructure are from 1.935µm to 2.778µm. The realized developed expert system with the integrated database is fully applicable for the observed hardware and software. Values of the arithmetic mean roughness and dimensional deviation indicate that casting substructures are surface quality, which is more than enough and useful for direct porcelain veneering. The manufacture of the substructure shows that the proposed ES allows the improvement of the design process while reducing the manufacturing time. Copyright © 2017 Elsevier B.V. All rights reserved.

Ten good reasons why everybody can and should perform cardiac ultrasound in the ICU.

PubMed

Charron, Cyril; Repessé, Xavier; Bodson, Laurent; Au, Siu-Ming; Vieillard-Baron, Antoine

2014-01-01

Critical care ultrasonography (CCUS) has been defined as an ultrasound evaluation of the heart, abdomen, pleura and lungs at the bedside by the intensivist, 24/7. Within CCUS, critical care echocardiography (CCE) is used to assess cardiac function and more generally haemodynamics. Experts in haemodynamics have published a 'consensus of 16' regarding an update on haemodynamic monitoring. They reported the ten key properties of an 'ideal' haemodynamic monitoring system, which perfectly match the ten good reasons we describe here for performing CCE in critically ill patients. Even though unfortunately no evidence-based medicine study is available to support this review, especially regarding CCE-related improvement of outcome, many clinical studies have demonstrated that CCE provides measurements of relevant, accurate, reproducible and interpretable variables, is easy to use, readily available, has a rapid response time, causes no harm, and is cost-effective. Whether it is operator-independent is obviously more debatable and is discussed in this review. All these characteristics are arguments for the extensive use of CCE by intensivists. This is why experts in the field have recommended that a basic level of CCE should be included in the training of all intensivists.

Automated space vehicle control for rendezvous proximity operations

NASA Technical Reports Server (NTRS)

Lea, Robert N.

1988-01-01

Rendezvous during the unmanned space exploration missions, such as a Mars Rover/Sample Return will require a completely automatic system from liftoff to docking. A conceptual design of an automated rendezvous, proximity operations, and docking system is being implemented and validated at the Johnson Space Center (JSC). The emphasis is on the progress of the development and testing of a prototype system for control of the rendezvous vehicle during proximity operations that is currently being developed at JSC. Fuzzy sets are used to model the human capability of common sense reasoning in decision making tasks and such models are integrated with the expert systems and engineering control system technology to create a system that performs comparably to a manned system.

Automated space vehicle control for rendezvous proximity operations

NASA Technical Reports Server (NTRS)

Lea, Robert N.

1988-01-01

Rendezvous during the unmanned space exploration missions, such as a Mars Rover/Sample Return will require a completely automatic system from liftoff to docking. A conceptual design of an automated rendezvous, proximity operations, and docking system is being implemented and validated at the Johnson Space Center (JSC). The emphasis is on the progress of the development and testing of a prototype system for control of the rendezvous vehicle during proximity operations that is currently being developed at JSC. Fuzzy sets are used to model the human capability of common sense reasoning in decision-making tasks and such models are integrated with the expert systems and engineering control system technology to create a system that performs comparably to a manned system.

Qualitative Understanding of Magnetism at Three Levels of Expertise

NASA Astrophysics Data System (ADS)

Stefani, Francesco; Marshall, Jill

2010-03-01

This work set out to investigate the state of qualitative understanding of magnetism at various stages of expertise, and what approaches to problem-solving are used across the spectrum of expertise. We studied three groups: 10 novices, 10 experts-in-training, and 11 experts. Data collection involved structured interviews during which participants solved a series of non-standard problems designed to test for conceptual understanding of magnetism. The interviews were analyzed using a grounded theory approach. None of the novices and only a few of the experts in training showed a strong understanding of inductance, magnetic energy, and magnetic pressure; and for the most part they tended not to approach problems visually. Novices frequently described gist memories of demonstrations, text book problems, and rules (heuristics). However, these fragmentary mental models were not complete enough to allow them to reason productively. Experts-in-training were able to solve problems that the novices were not able to solve, many times simply because they had greater recall of the material, and therefore more confidence in their facts. Much of their thinking was concrete, based on mentally manipulating objects. The experts solved most of the problems in ways that were both effective and efficient. Part of the efficiency derived from their ability to visualize and thus reason in terms of field lines.

Qualitative Understanding of Magnetism at Three Levels of Expertise

NASA Astrophysics Data System (ADS)

Stefani, Francesco; Marshall, Jill

2009-04-01

This work set out to investigate the state of qualitative understanding of magnetism at various stages of expertise, and what approaches to problem-solving are used across the spectrum of expertise. We studied three groups: 10 novices, 10 experts-in-training, and 11 experts. Data collection involved structured interviews during which participants solved a series of non-standard problems designed to test for conceptual understanding of magnetism. The interviews were analyzed using a grounded theory approach. None of the novices and only a few of the experts in training showed a strong understanding of inductance, magnetic energy, and magnetic pressure; and for the most part they tended not to approach problems visually. Novices frequently described gist memories of demonstrations, text book problems, and rules (heuristics). However, these fragmentary mental models were not complete enough to allow them to reason productively. Experts-in-training were able to solve problems that the novices were not able to solve, many times simply because they had greater recall of the material, and therefore more confidence in their facts. Much of their thinking was concrete, based on mentally manipulating objects. The experts solved most of the problems in ways that were both effective and efficient. Part of the efficiency derived from their ability to visualize and thus reason in terms of field lines.

Debating the legitimacy of a contested environmental illness: a case study of multiple chemical sensitivities (MCS).

PubMed

Phillips, Tarryn

2010-11-01

More than 20years after it was first identified, the anomalous condition, multiple chemical sensitivities (MCS), remains immersed in controversy, with a continuing debate over its causation being played out in the medico-scientific community and in the courts. This article examines why sceptical and supportive experts disagree over the condition's legitimacy as an organic condition. Drawing on ethnographic research conducted in Perth, Western Australia, the author scrutinises the decision-making practices of 16 experts (eight sceptical and eight supportive of a chemical explanation). Both groups were found to use evidence-based, inductive reasoning. However, sceptical experts tended to use a different set of evidence requirements, exhibited more faith in the efficiency of the current biomedical paradigm regarding toxicity and were less likely to acknowledge uncertainty in their field. All the experts recognised a spectrum of beliefs about the causal mechanisms of MCS. However, when they were engaged in litigation as expert witnesses due to their supportive or sceptical tendency, the oppositional legal system polarised their opinions and exacerbated the perceived divide between them. Ultimately, the adversarial medico-legal process inhibits genuine dialogue between some of the key players in the MCS debate, thus impeding understanding and consensus about the condition. © 2010 The Author. Sociology of Health & Illness © 2010 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.

Causal Reasoning in Medicine: Analysis of a Protocol.

ERIC Educational Resources Information Center

Kuipers, Benjamin; Kassirer, Jerome P.

1984-01-01

Describes the construction of a knowledge representation from the identification of the problem (nephrotic syndrome) to a running computer simulation of causal reasoning to provide a vertical slice of the construction of a cognitive model. Interactions between textbook knowledge, observations of human experts, and computational requirements are…

Critiquing: A Different Approach to Expert Computer Advice in Medicine

PubMed Central

Miller, Perry L.

1984-01-01

The traditional approach to computer-based advice in medicine has been to design systems which simulate a physician's decision process. This paper describes a different approach to computer advice in medicine: a critiquing approach. A critiquing system first asks how the physician is planning to manage his patient and then critiques that plan, discussing the advantages and disadvantages of the proposed approach, compared to other approaches which might be reasonable or preferred. Several critiquing systems are currently in different stages of implementation. The paper describes these systems and discusses the characteristics which make each domain suitable for critiquing. The critiquing approach may prove especially well-suited in domains where decisions involve a great deal of subjective judgement.

Fostering deliberations about health innovation: what do we want to know from publics?

PubMed

Lehoux, Pascale; Daudelin, Genevieve; Demers-Payette, Olivier; Boivin, Antoine

2009-06-01

As more complex and uncertain forms of health innovation keep emerging, scholars are increasingly voicing arguments in favour of public involvement in health innovation policy. The current conceptualization of this involvement is, however, somewhat problematic as it tends to assume that scientific facts form a "hard," indisputable core around which "soft," relative values can be attached. This paper, by giving precedence to epistemological issues, explores what there is to know from public involvement. We argue that knowledge and normative assumptions are co-constitutive of each other and pivotal to the ways in which both experts and non-experts reason about health innovations. Because knowledge and normative assumptions are different but interrelated ways of reasoning, public involvement initiatives need to emphasise deliberative processes that maximise mutual learning within and across various groups of both experts and non-experts (who, we argue, all belong to the "publics"). Hence, we believe that what researchers might wish to know from publics is how their reasoning is anchored in normative assumptions (what makes a given innovation desirable?) and in knowledge about the plausibility of their effects (are they likely to be realised?). Accordingly, one sensible goal of greater public involvement in health innovation policy would be to refine normative assumptions and make their articulation with scientific observations explicit and openly contestable. The paper concludes that we must differentiate between normative assumptions and knowledge, rather than set up a dichotomy between them or confound them.

Intelligent fault-tolerant controllers

NASA Technical Reports Server (NTRS)

Huang, Chien Y.

1987-01-01

A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.

1993-05-01

This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

Using Historical Knowledge to Reason about Contemporary Political Issues: An Expert-Novice Study

ERIC Educational Resources Information Center

Shreiner, Tamara L.

2014-01-01

People often justify history's place in the curriculum by its relationship to citizenship, yet there is little research to help educators picture how people use historical knowledge for civic purposes. This expert-novice study used the think-aloud method to examine how eight political scientists and eight high school students employed…

Can jurors recognize missing control groups, confounds, and experimenter bias in psychological science?

PubMed

McAuliff, Bradley D; Kovera, Margaret Bull; Nunez, Gabriel

2009-06-01

This study examined the ability of jury-eligible community members (N = 248) to detect internal validity threats in psychological science presented during a trial. Participants read a case summary in which an expert testified about a study that varied in internal validity (valid, missing control group, confound, and experimenter bias) and ecological validity (high, low). Ratings of expert evidence quality and expert credibility were higher for the valid versus missing control group versions only. Internal validity did not influence verdict or ratings of plaintiff credibility and no differences emerged as a function of ecological validity. Expert evidence quality, expert credibility, and plaintiff credibility were positively correlated with verdict. Implications for the scientific reasoning literature and for trials containing psychological science are discussed.

Production Systems as a Programming Language for Artificial Intelligence Applications. Volume III.

DTIC Science & Technology

1976-12-01

that the reader has some familiarity with Volume I of this report, which discusses the goals and conclusions of the thesis as a whole, and which...probably a suitable domain only for chess experts (which I am not), it will still be useful for the present thesis for the following reasons. As Berliner...chapters of this thesis do focus on such storage problems. Three other representational and low-level PS issues can be mentioned. Words are

Qualitative and temporal reasoning in engine behavior analysis

NASA Technical Reports Server (NTRS)

Dietz, W. E.; Stamps, M. E.; Ali, M.

1987-01-01

Numerical simulation models, engine experts, and experimental data are used to generate qualitative and temporal representations of abnormal engine behavior. Engine parameters monitored during operation are used to generate qualitative and temporal representations of actual engine behavior. Similarities between the representations of failure scenarios and the actual engine behavior are used to diagnose fault conditions which have already occurred, or are about to occur; to increase the surveillance by the monitoring system of relevant engine parameters; and to predict likely future engine behavior.

Expert Systems: An Overview for Teacher-Librarians.

ERIC Educational Resources Information Center

Orwig, Gary; Barron, Ann

1992-01-01

Provides an overview of expert systems for teacher librarians. Highlights include artificial intelligence and expert systems; the development of the MYCIN medical expert system; rule-based expert systems; the use of expert system shells to develop a specific system; and how to select an appropriate application for an expert system. (11 references)…

Clinical Reasoning in Athletic Training Education: Modeling Expert Thinking

ERIC Educational Resources Information Center

Geisler, Paul R.; Lazenby, Todd W.

2009-01-01

Objective: To address the need for a more definitive approach to critical thinking during athletic training educational experiences by introducing the clinical reasoning model for critical thinking. Background: Educators are aware of the need to teach students how to think critically. The multiple domains of athletic training are comprehensive and…

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

NASA Technical Reports Server (NTRS)

Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

1989-01-01

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

A conceptual framework for developing a critical thinking self-assessment scale.

PubMed

Nair, Girija G; Stamler, Lynnette Leeseberg

2013-03-01

Nurses must be talented critical thinkers to cope with the challenges related to the ever-changing health care system, population trends, and extended role expectations. Several countries now recognize critical thinking skills (CTS) as an expected outcome of nursing education programs. Critical thinking has been defined in multiple ways by philosophers, critical thinking experts, and educators. Nursing experts conceptualize critical thinking as a process involving cognitive and affective domains of reasoning. Nurse educators are often challenged with teaching and measuring CTS because of their latent nature and the lack of a uniform definition of the concept. In this review of the critical thinking literature, we examine various definitions, identify a set of constructs that define critical thinking, and suggest a conceptual framework on which to base a self-assessment scale for measuring CTS. Copyright 2013, SLACK Incorporated.

Understanding geological processes: Visualization of rigid and non-rigid transformations

NASA Astrophysics Data System (ADS)

Shipley, T. F.; Atit, K.; Manduca, C. A.; Ormand, C. J.; Resnick, I.; Tikoff, B.

2012-12-01

Visualizations are used in the geological sciences to support reasoning about structures and events. Research in cognitive sciences offers insights into the range of skills of different users, and ultimately how visualizations might support different users. To understand the range of skills needed to reason about earth processes we have developed a program of research that is grounded in the geosciences' careful description of the spatial and spatiotemporal patterns associated with earth processes. In particular, we are pursuing a research program that identifies specific spatial skills and investigates whether and how they are related to each other. For this study, we focus on a specific question: Is there an important distinction in the geosciences between rigid and non-rigid deformation? To study a general spatial thinking skill we employed displays with non-geological objects that had been altered by rigid change (rotation), and two types of non-rigid change ("brittle" (or discontinuous) and "ductile" (or continuous) deformation). Disciplinary scientists (geosciences and chemistry faculty), and novices (non-science faculty and undergraduate psychology students) answered questions that required them to visualize the appearance of the object before the change. In one study, geologists and chemists were found to be superior to non-science faculty in reasoning about rigid rotations (e.g., what an object would look like from a different perspective). Geologists were superior to chemists in reasoning about brittle deformations (e.g., what an object looked like before it was broken - here the object was a word cut into many fragments displaced in different directions). This finding is consistent with two hypotheses: 1) Experts are good at visualizing the types of changes required for their domain; and 2) Visualization of rigid and non-rigid changes are not the same skill. An additional important finding is that there was a broad range of skill in both rigid and non-rigid reasoning within the panels of science experts. In a second study, individual differences in reasoning about brittle deformations were correlated with reasoning about ductile deformations (e.g., what a bent plastic sheet would look like when unbent). Students who were good at visualizing what something looked like before it was broken were also good at visualizing what something looked like before it was bent, and this skill was not correlated to reasoning about rigid rotations. These findings suggest the cognitive processes that support reasoning about rigid and non-rigid events may differ and thus may require different types of support and training. We do not know if differences between experts and novices result from experience or self-selection, or both. Nevertheless, the range of spatial skill evinced by novices and experts strongly argues for designing visualizations to support a variety of users.

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE PAGES

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

2017-04-24

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Automated simulation as part of a design workstation

NASA Technical Reports Server (NTRS)

Cantwell, Elizabeth; Shenk, T.; Robinson, P.; Upadhye, R.

1990-01-01

A development project for a design workstation for advanced life-support systems (called the DAWN Project, for Design Assistant Workstation), incorporating qualitative simulation, required the implementation of a useful qualitative simulation capability and the integration of qualitative and quantitative simulation such that simulation capabilities are maximized without duplication. The reason is that to produce design solutions to a system goal, the behavior of the system in both a steady and perturbed state must be represented. The Qualitative Simulation Tool (QST), on an expert-system-like model building and simulation interface toll called ScratchPad (SP), and on the integration of QST and SP with more conventional, commercially available simulation packages now being applied in the evaluation of life-support system processes and components are discussed.

The role of communication in breast cancer screening: a qualitative study with Australian experts.

PubMed

Parker, Lisa M; Rychetnik, Lucie; Carter, Stacy M

2015-10-19

One well-accepted strategy for optimising outcomes in mammographic breast cancer screening is to improve communication with women about screening. It is not always clear, however, what it is that communication should be expected to achieve, and why or how this is so. We investigated Australian experts' opinions on breast screening communication. Our research questions were: 1 What are the views of Australian experts about communicating with consumers on breast screening? 2 How do experts reason about this topic? We used a qualitative methodology, interviewing 33 breast screening experts across Australia with recognisable influence in the Australian mammographic breast cancer screening setting. We used purposive and theoretical sampling to identify experts from different professional roles (including clinicians, program managers, policy makers, advocates and researchers) with a range of opinions about communication in breast screening. Experts discussed the topic of communication with consumers by focusing on two main questions: how strongly to guide consumers' breast cancer screening choices, and what to communicate about overdiagnosis. Each expert adopted one of three approaches to consumer communication depending on their views about these topics. We labelled these approaches: Be screened; Be screened and here's why; Screening is available please consider whether it's right for you. There was a similar level of support for all three approaches. Experts' reasoning was grounded in how they conceived of and prioritised their underlying values including: delivering benefits, avoiding harms, delivering more benefits than harms, respecting autonomy and transparency. There is disagreement between experts regarding communication with breast screening consumers. Our study provides some insights into this persisting lack of consensus, highlighting the different meanings that experts give to values, and different ways that values are prioritised. We suggest that explicit discussion about ethical values might help to focus thinking, clarify concepts and promote consensus in policy around communication with consumers. More specifically, we suggest that decision-makers who are considering policy on screening communication should begin with identifying and agreeing on the specific values to be prioritised and use this to guide them in establishing what the communication aims will be and which communication strategy will achieve those aims.

A preliminary study of the impact of a handover cognitive aid on clinical reasoning and information transfer.

PubMed

Weiss, Matthew J; Bhanji, Farhan; Fontela, Patricia S; Razack, Saleem I

2013-08-01

To assess the impact of a written cognitive aid on expressed clinical reasoning and quantity and the accuracy of information transfer during resident doctor handover. This study was a randomised controlled trial in an academic paediatric intensive care unit (PICU) of 20 handover events (10 events per group) from residents in their first PICU rotation using a written handover cognitive aid (intervention) or standard practice (control). Before rounds, an investigator generated a reference standard of the handover event by completing a handover aid. Resident handovers were then audio-recorded and transcribed by a blinded research assistant. The content of this transcript was inserted into a blank handover aid. A blinded content expert scored the quantity and accuracy of the information in this aid according to predetermined criteria and these information scores (ISs) were compared with the reference standard. The same expert also blindly scored the transcripts in five domains of clinical reasoning and effectiveness: (i) effective summary of events; (ii) expressed understanding of the care plan; (iii) presentation clarity; (iv) organisation; (v) overall handover effectiveness. Differences between intervention and control groups were assessed using the Mann-Whitney test and multivariate linear regression. The intervention group had total ISs that more closely approximated the reference standard (81% versus 61%; p < 0.01). The intervention group had significantly higher clinical reasoning scores when compared by total score (21.1 versus 15.9 points; p = 0.01) and in each of the five domains. No difference was observed in the duration of handover between groups (7.4 versus 7.7 minutes; p = 0.97). Using a novel scoring system, our simple handover cognitive aid was shown to improve information transfer and resident expression of clinical reasoning without prolonging the handover duration. © 2013 John Wiley & Sons Ltd.

[The debate concerning performance-based financing in Africa South of the Sahara: analysis of the nature].

PubMed

Manitu, Serge Mayaka; Meessen, Bruno; Lushimba, Michel Muvudi; Macq, Jean

2015-01-01

Performance-based financing (PBF) is a strategy designed to link thefunding of health services to predetermined results. Payment by an independent strategic purchaser is subject to verification of effective achievement of health outcomes in terms ofquantity and quality. This article investigates the complex tensions observed in relation to performance based financing (PBF) and identifies some reasons for disagreement on this approach. This study was essentially qualitative. Interviews were conducted with a panel of experts on PBF mobilizing their ability to reflect on the various arguments and positions concerning this financing mechanism. To enhance our analyses, we proposed a framework based on the main reasonsfor scientific or political controversies and factors involved in their emergence. Analysis of the information collected therefore consisted of combining experts verbatim reports with corresponding factors of controversies of our framework. Graphic representations of the differences were also established. Tensions concerning PBF are based on facts (experts' interpretation ofPBF), principles and values (around each expert's conceptual framework), balances of power between experts but also inappropriate behavior in the discussion process. Viewpoints remain isolated, each individual experience and an overview are lacking, which can interfere with decision-making and maintain the Health system reform crisis. Potential solutions to reduce these tensions are proposed. Our study shows that experts have difficulties agreeing on a theoretical priority approach to PBE. A good understanding of the nature of the tensions and an improvement in the quality of dialogue will promote a real dynamic of change and the proposal of an agenda of PBF actions.

A fuzzy logic approach toward solving the analytic enigma of health system financing.

PubMed

Chernichovsky, Dov; Bolotin, Arkady; de Leeuw, David

2003-09-01

Improved health, equity, macroeconomic efficiency, efficient provision of care, and client satisfaction are the common goals of any health system. The relative significance of these goals varies, however, across nations, communities and with time. As for health care finance, the attainment of these goals under varying circumstances involves alternative policy options for each of the following elements: sources of finance, allocation of finance, payment to providers, and public-private mix. The intricate set of multiple goals, elements and policy options defies human reasoning, and, hence, hinders effective policymaking. Indeed, "health system finance" is not amenable to a clear set of structural relationships. Neither is there a universe that can be subject to statistical scrutiny: each health system is unique. "Fuzzy logic" models human reasoning by managing "expert knowledge" close to the way it is handled by human language. It is used here for guiding policy making by a systematic analysis of health system finance. Assuming equal welfare weights for alternative goals and mutually exclusive policy options under each health-financing element, the exploratory model we present here suggests that a German-type health system is best. Other solutions depend on the welfare weights for system goals and mixes of policy options.

Combining human and machine processes (CHAMP)

NASA Astrophysics Data System (ADS)

Sudit, Moises; Sudit, David; Hirsch, Michael

2015-05-01

Machine Reasoning and Intelligence is usually done in a vacuum, without consultation of the ultimate decision-maker. The late consideration of the human cognitive process causes some major problems in the use of automated systems to provide reliable and actionable information that users can trust and depend to make the best Course-of-Action (COA). On the other hand, if automated systems are created exclusively based on human cognition, then there is a danger of developing systems that don't push the barrier of technology and are mainly done for the comfort level of selected subject matter experts (SMEs). Our approach to combining human and machine processes (CHAMP) is based on the notion of developing optimal strategies for where, when, how, and which human intelligence should be injected within a machine reasoning and intelligence process. This combination is based on the criteria of improving the quality of the output of the automated process while maintaining the required computational efficiency for a COA to be actuated in timely fashion. This research addresses the following problem areas: • Providing consistency within a mission: Injection of human reasoning and intelligence within the reliability and temporal needs of a mission to attain situational awareness, impact assessment, and COA development. • Supporting the incorporation of data that is uncertain, incomplete, imprecise and contradictory (UIIC): Development of mathematical models to suggest the insertion of a cognitive process within a machine reasoning and intelligent system so as to minimize UIIC concerns. • Developing systems that include humans in the loop whose performance can be analyzed and understood to provide feedback to the sensors.

Reconsidering Planning and Management of Medical Devices Procurement in Public Health Services in Cyprus

PubMed Central

Theodorou, Mamas; Georgiou, Marina; Nikolentzos, Athanasios; Bellali, Thalia

2015-01-01

Hospital procurement is a crucial field for any health care system, not only for economic reasons but also for reasons related to the quality and safety of the services provided. That is why the process of procurement is, in most countries, governed by a strict legal framework and policy mechanisms. This study investigates the problems and inefficiencies associated with the procurement of medical devices in public hospitals in Cyprus and formulates empirically documented proposals for improvement. Using the Delphi method, a group of 38 experts approach the procurement system in Cyprus from different angles, achieving high rates of consensus on 35 different statements on the weaknesses and problems of the current medical device procurement system, as well as presenting proposals and recommendations for improvement. The findings are highly valuable for future policy initiatives in Cyprus in the light of the economic crisis and the expected implementation of the new General Health Insurance System (GeSY), which the Government of the Republic of Cyprus and the Troika has agreed. PMID:26153175

Handheld echocardiographic screening for rheumatic heart disease by non-experts.

PubMed

Ploutz, Michelle; Lu, Jimmy C; Scheel, Janet; Webb, Catherine; Ensing, Greg J; Aliku, Twalib; Lwabi, Peter; Sable, Craig; Beaton, Andrea

2016-01-01

Handheld echocardiography (HAND) has good sensitivity and specificity for rheumatic heart disease (RHD) when performed by cardiologists. However, physician shortages in RHD-endemic areas demand less-skilled users to make RHD screening practical. We examine nurse performance and interpretation of HAND using a simplified approach for RHD screening. Two nurses received training on HAND and a simplified screening approach. Consented students at two schools in Uganda were eligible for participation. A simplified approach (HAND performed and interpreted by a non-expert) was compared with the reference standard (standard portable echocardiography, performed and interpreted by experts according to the 2012 World Heart Federation guidelines). Reasons for false-positive and false-negative HAND studies were identified. A total of 1002 children were consented, with 956 (11.1 years, 41.8% male) having complete data for review. Diagnoses included: 913 (95.5%) children were classified normal, 32 (3.3%) borderline RHD and 11 (1.2%) definite RHD. The simplified approach had a sensitivity of 74.4% (58.8% to 86.5%) and a specificity of 78.8% (76.0% to 81.4%) for any RHD (borderline and definite). Sensitivity improved to 90.9% (58.7% to 98.5%) for definite RHD. Identification and measurement of erroneous colour jets was the most common reason for false-positive studies (n=164/194), while missed mitral regurgitation and shorter regurgitant jet lengths with HAND were the most common reasons for false-negative studies (n=10/11). Non-expert-led HAND screening programmes offer a potential solution to financial and workforce barriers that limit widespread RHD screening. Nurses trained on HAND using a simplified approach had reasonable sensitivity and specificity for RHD screening. Information on reasons for false-negative and false-positive screening studies should be used to inform future training protocols, which could lead to improved screening performance. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Automatic Detection of Electric Power Troubles (ADEPT)

NASA Technical Reports Server (NTRS)

Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint; Brady, Mike; Ford, Donnie

1988-01-01

ADEPT is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system, and is designed for two modes of operation: real-time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a Laser printer. This system consists of a simulated Space Station power module using direct-current power supplies for Solar arrays on three power busses. For tests of the system's ability to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three busses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modelling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base. A load scheduler and a fault recovery system are currently under development to support both modes of operation.

An advanced artificial intelligence tool for menu design.

PubMed

Khan, Abdus Salam; Hoffmann, Achim

2003-01-01

The computer-assisted menu design still remains a difficult task. Usually knowledge that aids in menu design by a computer is hard-coded and because of that a computerised menu planner cannot handle the menu design problem for an unanticipated client. To address this problem we developed a menu design tool, MIKAS (menu construction using incremental knowledge acquisition system), an artificial intelligence system that allows the incremental development of a knowledge-base for menu design. We allow an incremental knowledge acquisition process in which the expert is only required to provide hints to the system in the context of actual problem instances during menu design using menus stored in a so-called Case Base. Our system incorporates Case-Based Reasoning (CBR), an Artificial Intelligence (AI) technique developed to mimic human problem solving behaviour. Ripple Down Rules (RDR) are a proven technique for the acquisition of classification knowledge from expert directly while they are using the system, which complement CBR in a very fruitful way. This combination allows the incremental improvement of the menu design system while it is already in routine use. We believe MIKAS allows better dietary practice by leveraging a dietitian's skills and expertise. As such MIKAS has the potential to be helpful for any institution where dietary advice is practised.

Problem-Solving Processes of Expert and Typical School Principals: A Quantitative Look

ERIC Educational Resources Information Center

Brenninkmeyer, Lawrence D.; Spillane, James P.

2008-01-01

Principals are increasingly expected to be the instructional as well as administrative leaders of their schools. However, little is known about how principals reason through the instructional issues that they face. An analysis of principal reasoning in instructional contexts is critical. The study presented in this article draws on interviews with…

The Importance of Teaching Methodology in Moral Education of Sport Populations.

ERIC Educational Resources Information Center

Stoll, Sharon Kay; And Others

Three approaches to teaching moral reasoning were implemented by expert teachers in classes at three small colleges and outcomes were compared. Teaching models included the following: Model A, a "good reasoned" approach in which students discussed scenarios and determined the best course of action; Model B, a teacher-centered lecture,…

Validation of the Quantitative Diagnostic Thinking Inventory for Athletic Training: A Pilot Study

ERIC Educational Resources Information Center

Kicklighter, Taz; Barnum, Mary; Geisler, Paul R.; Martin, Malissa

2016-01-01

Context: The cognitive process of making a clinical decision lies somewhere on a continuum between novices using hypothetico-deductive reasoning and experts relying more on case pattern recognition. Although several methods exist for measuring facets of clinical reasoning in specific situations, none have been experimentally applied, as of yet, to…

[Expertise test in the new Civil Prosecution Law (Law 1/2000)].

PubMed

Laborda Calvo, E

2004-12-01

Expertise test was the object of many controversies in the previous Civil Prosecution Law (CPL) from the way of naming the experts to the difficulties in the receiving payment. The new CPL uses the social process as model and provides civil justice with an agile and guaranteeing procedure. The CPL provides the expert test with a greater amplitude and new range, and should be used at the time of the lawsuit and openly seen. The experts should assume the defense of their arguments and be subjected to the objections of the contrary party. The expert's test becomes a mixed documental and personal test. It also modifies the way of naming the experts and the acceptance that may condition the allocation of funds in the amount considered necessary. The objection is limited to the experts named judicially, it being possible to eliminate them, however, the reason for it should be justified.

Validation of an Instrument to Assess the Mental Capacity to Sign an Enduring Power of Attorney.

PubMed

Ko, R Sf; Lui, V Wc; Lai, K C; Chiu, C Cy; Lam, L Cw

2017-03-01

To describe the validation of an instrument to assess the mental capacity of an individual to sign an enduring power of attorney. An instrument named Capacity Assessment to Sign an Enduring Power of Attorney (CASEPA) was developed following a literature review, focus group discussions, expert reviews, and pilot testing. Chinese persons aged ≥ 60 years who had a range of cognitive abilities were recruited from elderly care centres in Hong Kong to explore its psychometric properties. A total of 85 participants were included. For inter-rater reliability, the intraclass correlation coefficient was 0.93 for understanding, 0.87 for appreciation, and 0.84 for reasoning. For internal consistency, the Cronbach's alpha was 0.75 for understanding, 0.74 for appreciation, and 0.86 for reasoning. The content validity was examined by an international expert in mental capacity and psychiatry and by 5 local experts in the fields of mental health, law, psychiatry, psychology, and geriatrics. The clinician ratings correlated with the ability score for understanding (r = 0.74, p < 0.001), appreciation (r = 0.73, p < 0.001) and reasoning (r = 0.73, p < 0.001). The CASEPA is a potentially useful tool to assess the mental capacity of an individual to sign an enduring power of attorney.

Automatic Detection of Electric Power Troubles (ADEPT)

NASA Technical Reports Server (NTRS)

Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint; Brady, Mike; Ford, Donnie

1988-01-01

Automatic Detection of Electric Power Troubles (A DEPT) is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system. It is designed for two modes of operation: real time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a laser printer. This system consists of a simulated space station power module using direct-current power supplies for solar arrays on three power buses. For tests of the system's ablilty to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three buses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modeling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base.

Automatic Detection of Electric Power Troubles (ADEPT)

NASA Astrophysics Data System (ADS)

Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint; Brady, Mike; Ford, Donnie

1988-11-01

Automatic Detection of Electric Power Troubles (A DEPT) is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system. It is designed for two modes of operation: real time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a laser printer. This system consists of a simulated space station power module using direct-current power supplies for solar arrays on three power buses. For tests of the system's ablilty to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three buses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modeling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base.

Expert Systems: An Overview.

ERIC Educational Resources Information Center

Adiga, Sadashiv

1984-01-01

Discusses: (1) the architecture of expert systems; (2) features that distinguish expert systems from conventional programs; (3) conditions necessary to select a particular application for the development of successful expert systems; (4) issues to be resolved when building expert systems; and (5) limitations. Examples of selected expert systems…

Knowledge Preservation for Design of Rocket Systems

NASA Technical Reports Server (NTRS)

Moreman, Douglas

2002-01-01

An engineer at NASA Lewis RC presented a challenge to us at Southern University. Our response to that challenge, stated circa 1993, has evolved into the Knowledge Preservation Project which is here reported. The stated problem was to capture some of the knowledge of retiring NASA engineers and make it useful to younger engineers via computers. We evolved that initial challenge to this - design a system of tools such that, with this system, people might efficiently capture and make available via commonplace computers, deep knowledge of retiring NASA engineers. In the process of proving some of the concepts of this system, we would (and did) capture knowledge from some specific engineers and, so, meet the original challenge along the way to meeting the new. Some of the specific knowledge acquired, particularly that on the RL- 10 engine, was directly relevant to design of rocket engines. We considered and rejected some of the techniques popular in the days we began - specifically "expert systems" and "oral histories". We judged that these old methods had too high a cost per sentence preserved. That cost could be measured in hours of labor of a "knowledge professional". We did spend, particularly in the grant preceding this one, some time creating a couple of "concept maps", one of the latest ideas of the day, but judged this also to be costly in time of a specially trained knowledge-professional. We reasoned that the cost in specialized labor could be lowered if less time were spent being selective about sentences from the engineers and in crafting replacements for those sentences. The trade-off would seem to be that our set of sentences would be less dense in information, but we found a computer-based way around this seeming defect. Our plan, details of which we have been carrying out, was to find methods of extracting information from experts which would be capable of gaining cooperation, and interest, of senior engineers and using their time in a way they would find worthy (and, so, they would give more of their time and recruit time of other engineers as well). We studied these four ways of creating text: 1) the old way, via interviews and discussions - one of our team working with one expert, 2) a group-discussion led by one of the experts themselves and on a topic which inspires interaction of the experts, 3) a spoken dissertation by one expert practiced in giving talks, 4) expropriating, and modifying for our system, some existing reports (such as "oral histories" from the Smithsonian Institution).

Examing nursing students' understanding of the cardiovascular system in a BSN program

NASA Astrophysics Data System (ADS)

Stuart, Parker Emerson

This study investigated the alignment of important cardiovascular system (CVS) concepts identified by expert nurses with nursing student's knowledge. Specifically, it focused on the prevalence of nursing students' alternative conceptions for these important concepts as a potential reason for a theory-practice gap in nursing (Corlett, 2000; Jordan, 1994). This is the first study to target nursing student alternative conceptions exclusively whereas other studies focused on diverse groups of undergraduates' CVS knowledge (Michael et al., 2002). The study was divided into two phases and used a case study approach with each phase of the study representing a single case. The first phase of the study sought to understand what CVS concepts expert nurses deemed relevant to their daily practice and how these experts used these concepts. The second phase identified nursing student alternative conceptions through the use of open-ended scenarios based on the results of phase I. For the first phase of the study involved four CVS expert nurses practicing in emergency rooms and cardiac intensive care units at two local hospitals. Interviews were used to elicit important CVS concepts. The expert nurses identified five broad concepts as important to their practice. These concepts were a) cardiovascular anatomical concepts; b) cardiovascular physiological concepts; c) homeostasis and diseases of the CVS; d) the interdependence and interaction of the CVS with other organ systems and e) the intersection of the CVS and technology in patient diagnosis and treatment. These finding reinforce concepts already being taught to nursing students but also suggest that instruction should focus more on how the CVS interacts with other organ systems and how technology and the CVS interact. The presence of alternative conceptions in the nursing students was examined through the use of open-ended questions. A total of 17 students fully completed the scenario questions. Results indicate that this group of nursing students hold some CVS alternative conceptions. Overall, the alternative conceptions can be grouped into four categories: a) CVS anatomy, b) blood flow and pressure, c) anthropomorphic views and d) miscellaneous alternative conceptions. These findings suggest there is indeed a misalignment between expert nurses' and nursing students' knowledge of the CVS with this misalignment potentially contributing to the theory-practice gap.

How Four Scientists Integrate Thermodynamic and Kinetic Theory, Context, Analogies, and Methods in Protein-Folding and Dynamics Research: Implications for Biochemistry Instruction

ERIC Educational Resources Information Center

Jeffery, Kathleen A.; Pelaez, Nancy; Anderson, Trevor R.

2018-01-01

To keep biochemistry instruction current and relevant, it is crucial to expose students to cutting-edge scientific research and how experts reason about processes governed by thermodynamics and kinetics such as protein folding and dynamics. This study focuses on how experts explain their research into this topic with the intention of informing…

A Modified Delphi to Identify the Significant Works Pertaining to the Understanding of Reading Comprehension and Content Analysis of the Identified Works

ERIC Educational Resources Information Center

Zunker, Norma D.; Pearce, Daniel L.

2012-01-01

The first part of this study explored the significant works pertaining to the understanding of reading comprehension using a Modified Delphi Method. A panel of reading comprehension experts identified 19 works they considered to be significant to the understanding of reading comprehension. The panel of experts identified the reasons they…

Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

PubMed

Elkin, Peter L; Schlegel, Daniel R; Anderson, Michael; Komm, Jordan; Ficheur, Gregoire; Bisson, Leslie

2018-04-01

Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with self-diagnosis of knee problems and to thereby facilitate referral to the right orthopedic subspecialist. They had two independent sports medicine physicians review 469 cases. A board-certified orthopedic sports medicine practitioner, L.B., reviewed any disagreements until a gold standard diagnosis was reached. For each case, the patients entered 126 potential answers to 26 questions into a Web interface. These were modeled by an expert sports medicine physician and the answers were reviewed by L.B. For each finding, the clinician specified the sensitivity (term frequency) and both specificity (Sp) and the heuristic evoking strength (ES). Heuristics are methods of reasoning with only partial evidence. An expert system was constructed that reflected the posttest odds of disease-ranked list for each case. We compare the accuracy of using Sp to that of using ES (original model, p  < 0.0008; term importance * disease importance [DItimesTI] model, p  < 0.0001: Wilcoxon ranked sum test). For patient referral assignment, Sp in the DItimesTI model was superior to the use of ES. By the fifth diagnosis, the advantage was lost and so there is no difference between the techniques when serving as a reminder system. Schattauer GmbH Stuttgart.

Expert systems in civil engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostem, C.N.; Maher, M.L.

1986-01-01

This book presents the papers given at a symposium on expert systems in civil engineering. Topics considered at the symposium included problem solving using expert system techniques, construction schedule analysis, decision making and risk analysis, seismic risk analysis systems, an expert system for inactive hazardous waste site characterization, an expert system for site selection, knowledge engineering, and knowledge-based expert systems in seismic analysis.

Cyber nursing--health 'experts' approaches in the post-modern era of virtual performances: a nethnography study.

PubMed

Eriksson, Henrik; Salzmann-Erikson, Martin

2013-03-01

The imperative to gather information online and to become an 'expert' by locating effective advice for oneself and others is a fairly new support phenomenon in relation to health advice. The creation of new positions for health 'experts' within the space of the Internet has been addressed as a cybernursing activity. A focused analysis of communication in health forums might give insight into the new roles that are available for health experts in cyberspace. The aim of this study is to describe approaches to being an 'expert' in lifestyle health choice forums on the Internet and to elaborate on the communicative performances that take place in the forums. An archival and cross-sectional observational forum study was undertaken using principles for conducting ethnographic research online. 2640 pages of data from two health Internet forums were gathered and analyzed. The results reveal three distinctive types of experts that emerge in the forums: (1) those that build their expertise by creating a presence in the forum based on lengthy and frequent postings, (2) those who build a presence through reciprocal exchanges with individual posters with questions or concerns, and (3) those who build expertise around a "life long learning" perspective based on logic and reason. The results suggest that experts not only co-exist in the forums, but more importantly they reinforce each others' positions. This effect is central; alongside one another, the posts of the three types of experts we identify constitute a whole for those seeking the forum for advice and support. Users are provided with strong opinions and advice, support and Socratic reasoning, and a problem-oriented approach. The Internet is now an integral part of everyday living, not least of which among those who seek and offer support in cyberspace. As such, cyber nursing has become an important activity to monitor, and formal health care professionals and nursing researchers must stay abreast of developments. Copyright © 2012 Elsevier Ltd. All rights reserved.

A bird's eye view: the cognitive strategies of experts interpreting seismic profiles

NASA Astrophysics Data System (ADS)

Bond, C. E.; Butler, R.

2012-12-01

Geoscience is perhaps unique in its reliance on incomplete datasets and building knowledge from their interpretation. This interpretation basis for the science is fundamental at all levels; from creation of a geological map to interpretation of remotely sensed data. To teach and understand better the uncertainties in dealing with incomplete data we need to understand the strategies individual practitioners deploy that make them effective interpreters. The nature of interpretation is such that the interpreter needs to use their cognitive ability in the analysis of the data to propose a sensible solution in their final output that is both consistent not only with the original data but also with other knowledge and understanding. In a series of experiments Bond et al. (2007, 2008, 2011, 2012) investigated the strategies and pitfalls of expert and non-expert interpretation of seismic images. These studies focused on large numbers of participants to provide a statistically sound basis for analysis of the results. The outcome of these experiments showed that techniques and strategies are more important than expert knowledge per se in developing successful interpretations. Experts are successful because of their application of these techniques. In a new set of experiments we have focused on a small number of experts to determine how they use their cognitive and reasoning skills, in the interpretation of 2D seismic profiles. Live video and practitioner commentary were used to track the evolving interpretation and to gain insight on their decision processes. The outputs of the study allow us to create an educational resource of expert interpretation through online video footage and commentary with associated further interpretation and analysis of the techniques and strategies employed. This resource will be of use to undergraduate, post-graduate, industry and academic professionals seeking to improve their seismic interpretation skills, develop reasoning strategies for dealing with incomplete datasets, and for assessing the uncertainty in these interpretations. Bond, C.E. et al. (2012). 'What makes an expert effective at interpreting seismic images?' Geology, 40, 75-78. Bond, C. E. et al. (2011). 'When there isn't a right answer: interpretation and reasoning, key skills for 21st century geoscience'. International Journal of Science Education, 33, 629-652. Bond, C. E. et al. (2008). 'Structural models: Optimizing risk analysis by understanding conceptual uncertainty'. First Break, 26, 65-71. Bond, C. E. et al., (2007). 'What do you think this is?: "Conceptual uncertainty" In geoscience interpretation'. GSA Today, 17, 4-10.

Expert system application for the loading capability assessment of transmission lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le, T.L.; Negnevitsky, M.; Piekutowski, M.

1995-11-01

This paper describes the application of an expert system for the evaluation of the short time thermal rating and temperature rise of overhead conductors. The expert system has been developed using a database and Leonardo expert system shell which is gaining popularity among commercial tools for developing expert system applications. The expert system has been found to compare well when evaluated against the site tests. A practical application is given to demonstrate the usefulness of the expert system developed.

Comparative study of forensic psychiatric system between China and America.

PubMed

Li, Gangqin; Gutheil, Thomas G; Hu, Zeqing

2016-01-01

Laws and regulations about the forensic psychiatric systems in China and America were compared, and suggestions for improving the forensic psychiatric system of China were provided. There are many differences regarding the role of the forensic psychiatrist, the initiation of the assessment and the admission of expert opinion because of elements in the legal systems in China and America. The Chinese system has the advantages of objectivity, cost saving and high efficiency; but it has deficiencies in procedural justice and the admission of expert opinion. China can persist with the current system while taking measures to give more rights to the litigants to participate in their assessment, and while improving the quality and utility of the expert opinion; however, this review article will compare broadly the two systems without addressing human rights issues or procedural justice issues, nor will it presume to address the entirety of Chinese systems. In addition, China is developing its legal system for dealing with the mentally ill defendant in situations involving the criminal justice system and civil commitment. Although China enacted new laws regarding the mandatory treatment for the mentally ill, both in criminal and civil systems, there remain many aspects to be improved, including but not limited to a system of review of the decision to detain a patient on psychiatric grounds, and the need for provisions in the laws preventing indefinite detention. From this viewpoint, America's laws and regulations are instructive for us, in matters such as the method of dealing with the mentally ill defendant who is "incompetent to stand trial", "not guilty only by reason of insanity" or "guilty but mentally ill". The conditional release of the committed mentally ill person and the special programs in the forensic security hospital are all worthy of study by China in order to manage the mentally ill offender and to reduce the recidivism rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Architectures for reasoning in parallel

NASA Technical Reports Server (NTRS)

Hall, Lawrence O.

1989-01-01

The research conducted has dealt with rule-based expert systems. The algorithms that may lead to effective parallelization of them were investigated. Both the forward and backward chained control paradigms were investigated in the course of this work. The best computer architecture for the developed and investigated algorithms has been researched. Two experimental vehicles were developed to facilitate this research. They are Backpac, a parallel backward chained rule-based reasoning system and Datapac, a parallel forward chained rule-based reasoning system. Both systems have been written in Multilisp, a version of Lisp which contains the parallel construct, future. Applying the future function to a function causes the function to become a task parallel to the spawning task. Additionally, Backpac and Datapac have been run on several disparate parallel processors. The machines are an Encore Multimax with 10 processors, the Concert Multiprocessor with 64 processors, and a 32 processor BBN GP1000. Both the Concert and the GP1000 are switch-based machines. The Multimax has all its processors hung off a common bus. All are shared memory machines, but have different schemes for sharing the memory and different locales for the shared memory. The main results of the investigations come from experiments on the 10 processor Encore and the Concert with partitions of 32 or less processors. Additionally, experiments have been run with a stripped down version of EMYCIN.

49 CFR 6.11 - Allowable fees and expenses.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) No award for the fee of an attorney or agent under these rules may exceed $125.00 per hour. This... expert witnesses, or $24.09 per hour, whichever is less. (c) In determining the reasonableness of the fee... factors as may bear on the value of the services provided. (d) The reasonable cost of any study, analysis...

49 CFR 6.11 - Allowable fees and expenses.

Code of Federal Regulations, 2011 CFR

2011-10-01

...) No award for the fee of an attorney or agent under these rules may exceed $125.00 per hour. This... expert witnesses, or $24.09 per hour, whichever is less. (c) In determining the reasonableness of the fee... factors as may bear on the value of the services provided. (d) The reasonable cost of any study, analysis...

Does Medical Students' Diagnostic Performance Improve by Observing Examples of Self-Explanation Provided by Peers or Experts?

ERIC Educational Resources Information Center

Chamberland, Martine; Mamede, Sílvia; St-Onge, Christina; Setrakian, Jean; Schmidt, Henk G.

2015-01-01

Educational strategies that promote the development of clinical reasoning in students remain scarce. Generating self-explanations (SE) engages students in active learning and has shown to be an effective technique to improve clinical reasoning in clerks. Example-based learning has been shown to support the development of accurate knowledge…

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

NASA Astrophysics Data System (ADS)

Leon, Barbara D.; Heller, Paul R.

1987-05-01

A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system, driven by a forward chaining inference engine, makes decisions based on the global database. The global database contains current track and sensor information supplied by the simulation. At present, the rule base emphasizes the surveillance features with rules grouped into three main categories: maintenance and enhancing track on prioritized targets; filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.

Defense Small Business Innovation Research Program (SBIR). Volume 4. Defense Agency Projects, Abstracts of Phase 1 Awards from FY 1989 SBIR Solicitation

DTIC Science & Technology

1990-04-01

EXPLOSIVE ACTIVITY . FINDINGS AND MEASUREMENTS FROM EACH IMAGE WILL BE COMBINED IN A GEOGRAPHIC INFORMATION DATA BASE . VARIOUS IMAGE AND MAP PROJECTS WILL BE...PROPOSAL OF LAND MINES DETECTION BY A NUCLEAR ACTIVATION METHOD IS BASED ON A NEW EXTREMELY INTENSE, COMPACT PULSED SOURCE OF 14.1 MeV NEUTRONS (WITH A...CONVENTIONAL KNOWLEDGE- BASED SYSTEMS TOPIC# 38 OFFICE: PM/SBIR IDENT#: 33862 CASE- BASED REASONING (CBR) REPRESENTS A POWERFUL NEW PARADIGM FOR BUILDING EXPERT

Adaptive Sampling using Support Vector Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

Of Pigs and Men: Understanding Students' Reasoning About the Use of Pigs as Donors for Xenotransplantation

NASA Astrophysics Data System (ADS)

Lindahl, Mats Gunnar

2010-09-01

Two important roles of education are to provide students with knowledge for their democratic participation in society and to provide knowledge for a future profession. In science education, students encounter values that may be in conflict with their worldview. Such conflicts may, for example, lead to constructive reflections as well as rejection of scientific knowledge and technology. Students’ ways of reasoning are important starting points for discussing problematic issues and may be crucial for constructive dialogues in the classroom. This study investigates students’ reasoning about conflicting values concerning the human-animal relationship exemplified by the use of genetically modified pigs as organ donors for xenotransplantation. Students’ reasoning is analyzed using Giddens’ concepts of disembedded and embedded practices in parallel with moral philosophical theories in a framework based on human-animal relationships. Thirteen students were interviewed and their stances categorized. Kantian deontological and classical utilitarian ethics were found within the patronage and the partnership models. These students appreciated expert knowledge but those using the partnership model could not accept xenotransplantation if pigs were to be killed. Students using care ethics did not appreciate expert knowledge since it threatened naturalness. The results suggest that stances against the use of scientific knowledge are more problematic than knowledge per se, and that conflicting stances have similarities that present opportunities for understanding and development of students’ argumentation skills for future participation in societal discourse on utilizing expert knowledge. Furthermore it is argued that science education could benefit from a higher awareness of the presence of different morals.

Faults Discovery By Using Mined Data

NASA Technical Reports Server (NTRS)

Lee, Charles

2005-01-01

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Cognition of an expert tackling an unfamiliar conceptual physics problem

NASA Astrophysics Data System (ADS)

Schuster, David; Undreiu, Adriana

2009-11-01

We have investigated and analyzed the cognition of an expert tackling a qualitative conceptual physics problem of an unfamiliar type. Our goal was to elucidate the detailed cognitive processes and knowledge elements involved, irrespective of final solution form, and consider implications for instruction. The basic but non-trivial problem was to find qualitatively the direction of acceleration of a pendulum bob at various stages of its motion, a problem originally studied by Reif and Allen. Methodology included interviews, introspection, retrospection and self-reported metacognition. Multiple facets of cognition were revealed, with different reasoning strategies used at different stages and for different points on the path. An account is given of the zigzag thinking paths and interplay of reasoning modes and schema elements involved. We interpret the cognitive processes in terms of theoretical concepts that emerged, namely: case-based, principle-based, experiential-intuitive and practical-heuristic reasoning; knowledge elements and schemata; activation; metacognition and epistemic framing. The complexity of cognition revealed in this case study contrasts with the tidy principle-based solutions we present to students. The pervasive role of schemata, case-based reasoning, practical heuristic strategies, and their interplay with physics principles is noteworthy, since these aspects of cognition are generally neither recognized nor taught. The schema/reasoning-mode perspective has direct application in science teaching, learning and problem-solving.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

NESSUS/EXPERT - An expert system for probabilistic structural analysis methods

NASA Technical Reports Server (NTRS)

Millwater, H.; Palmer, K.; Fink, P.

1988-01-01

An expert system (NESSUS/EXPERT) is presented which provides assistance in using probabilistic structural analysis methods. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator. NESSUS/EXPERT was developed with a combination of FORTRAN and CLIPS, a C language expert system tool, to exploit the strengths of each language.

Case-Based Capture and Reuse of Aerospace Design Rationale

NASA Technical Reports Server (NTRS)

Leake, David B.

2001-01-01

The goal of this project was to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project combined case-based reasoning (CBR) and concept maps (CMaps) to develop methods for capturing, organizing, and interactively accessing records of experiences encapsulating the methods and rationale underlying expert aerospace design, in order to bring the captured knowledge to bear to support future reasoning. The project's results contribute both principles and methods for effective design-aiding systems that aid capture and access of useful design knowledge. The project has been guided by the tenets that design-aiding systems must: (1) Leverage a designer's knowledge, rather than attempting to replace it; (2) Be able to reflect different designers' differing conceptualizations of the design task, and to clarify those conceptualizations to others; (3) Include capabilities to capture information both by interactive knowledge modeling and during normal use; and (4) Integrate into normal designer tasks as naturally and unobtrusive as possible.

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

NASA Technical Reports Server (NTRS)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

Wumpus Advisor I. A First Implementation of a Program That Tutors Logical and Probabilistic Reasoning Skills. AI Memo 381.

ERIC Educational Resources Information Center

Stansfield, James L.; And Others

An Intelligent Computer Aided Instruction (ICAI) program that incorporates an Expert module which allows the tutor to compare the student's response to those generated by an expert was developed for use with Wumpus, a simple maze-exploration game. The Wumpus Advisor program offers advice to a player involved in choosing the best move in a game for…

Assessment of clinical reasoning: A Script Concordance test designed for pre-clinical medical students.

PubMed

Humbert, Aloysius J; Johnson, Mary T; Miech, Edward; Friedberg, Fred; Grackin, Janice A; Seidman, Peggy A

2011-01-01

The Script Concordance test (SCT) measures clinical reasoning in the context of uncertainty by comparing the responses of examinees and expert clinicians. It uses the level of agreement with a panel of experts to assign credit for the examinee's answers. This study describes the development and validation of a SCT for pre-clinical medical students. Faculty from two US medical schools developed SCT items in the domains of anatomy, biochemistry, physiology, and histology. Scoring procedures utilized data from a panel of 30 expert physicians. Validation focused on internal reliability and the ability of the SCT to distinguish between different cohorts. The SCT was administered to an aggregate of 411 second-year and 70 fourth-year students from both schools. Internal consistency for the 75 test items was satisfactory (Cronbach's alpha = 0.73). The SCT successfully differentiated second- from fourth-year students and both student groups from the expert panel in a one-way analysis of variance (F(2,508) = 120.4; p < 0.0001). Mean scores for students from the two schools were not significantly different (p = 0.20). This SCT successfully differentiated pre-clinical medical students from fourth-year medical students and both cohorts of medical students from expert clinicians across different institutions and geographic areas. The SCT shows promise as an easy-to-administer measure of "problem-solving" performance in competency evaluation even in the beginning years of medical education.

Section-constrained local geological interface dynamic updating method based on the HRBF surface

NASA Astrophysics Data System (ADS)

Guo, Jiateng; Wu, Lixin; Zhou, Wenhui; Li, Chaoling; Li, Fengdan

2018-02-01

Boundaries, attitudes and sections are the most common data acquired from regional field geological surveys, and they are used for three-dimensional (3D) geological modelling. However, constructing topologically consistent 3D geological models from rapid and automatic regional modelling with convenient local modifications remains unresolved. In previous works, the Hermite radial basis function (HRBF) surface was introduced for the simulation of geological interfaces from geological boundaries and attitudes, which allows 3D geological models to be automatically extracted from the modelling area by the interfaces. However, the reasonability and accuracy of non-supervised subsurface modelling is limited without further modifications generated through explanations and analyses performed by geology experts. In this paper, we provide flexible and convenient manual interactive manipulation tools for geologists to sketch constraint lines, and these tools may help geologists transform and apply their expert knowledge to the models. In the modified modelling workflow, the geological sections were treated as auxiliary constraints to construct more reasonable 3D geological models. The geometric characteristics of section lines were abstracted to coordinates and normal vectors, and along with the transformed coordinates and vectors from boundaries and attitudes, these characteristics were adopted to co-calculate the implicit geological surface function parameters of the HRBF equations and form constrained geological interfaces from topographic (boundaries and attitudes) and subsurface data (sketched sections). Based on this new modelling method, a prototype system was developed, in which the section lines could be imported from databases or interactively sketched, and the models could be immediately updated after the new constraints were added. Experimental comparisons showed that all boundary, attitude and section data are well represented in the constrained models, which are consistent with expert explanations and help improve the quality of the models.

Conceptualizing movement by expert Bobath instructors in neurological rehabilitation.

PubMed

Vaughan-Graham, Julie; Patterson, Kara; Zabjek, Karl; Cott, Cheryl A

2017-12-01

Movement, a core aspect of physiotherapy practice, and integral to the clinical reasoning process has undergone limited theoretical development. Instead, research has focused on intervention effectiveness embedded within the positivist paradigm. The purpose of this study was to explore how expert neurorehabilitation therapists conceptualize movement as part of their clinical reasoning. A qualitative interpretive descriptive approach consisting of stimulated recall using video-recorded treatment sessions and in-depth interviews was used. Theoretical sampling was used to recruit members of the International Bobath Instructors Training Association (IBITA) who are recognized experts in neurorehabilitation. Interview transcripts were transcribed verbatim. Data analysis was progressive, iterative, and inductive. Twenty-two IBITA instructors from 7 different countries volunteered to participate. They ranged in clinical experience from 12 to 40 years and instructor experience from 1 to 35 years. The conceptualization of movement by the IBITA instructors involves the following elements: (1) movement comprises the whole person and the whole body, not just individual body segments; (2) active alignment of body segments is integral to movement performance; and (3) efficient movement requires the relative integration of postural control/stability and selective movement/mobility. The IBITA instructors conceptualize movement from a person-centred perspective. The integration of postural control and selective movement, with alignment and variability as key components, forms the foundation of their understanding of movement. Further investigation into the role of postural control in movement recovery post central nervous system lesion is required. Likewise, the dimensions of movement critical to the conceptualization of movement are not well understood from the perspective of the physiotherapist or persons with neurological impairments. © 2017 John Wiley & Sons, Ltd.

Automated screening of propulsion system test data by neural networks, phase 1

NASA Technical Reports Server (NTRS)

Hoyt, W. Andes; Whitehead, Bruce A.

1992-01-01

The evaluation of propulsion system test and flight performance data involves reviewing an extremely large volume of sensor data generated by each test. An automated system that screens large volumes of data and identifies propulsion system parameters which appear unusual or anomalous will increase the productivity of data analysis. Data analysts may then focus on a smaller subset of anomalous data for further evaluation of propulsion system tests. Such an automated data screening system would give NASA the benefit of a reduction in the manpower and time required to complete a propulsion system data evaluation. A phase 1 effort to develop a prototype data screening system is reported. Neural networks will detect anomalies based on nominal propulsion system data only. It appears that a reasonable goal for an operational system would be to screen out 95 pct. of the nominal data, leaving less than 5 pct. needing further analysis by human experts.

Fullerene data mining using bibliometrics and database tomography

PubMed

Kostoff; Braun; Schubert; Toothman; Humenik

2000-01-01

Database tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multiword phrase frequencies and phrase proximities (physical closeness of the multiword technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT was used to derive technical intelligence from a fullerenes database derived from the Science Citation Index and the Engineering Compendex. Phrase frequency analysis by the technical domain experts provided the pervasive technical themes of the fullerenes database, and phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the fullerenes literature supplemented the DT results with author/journal/institution publication and citation data. Comparisons of fullerenes results with past analyses of similarly structured near-earth space, chemistry, hypersonic/supersonic flow, aircraft, and ship hydrodynamics databases are made. One important finding is that many of the normalized bibliometric distribution functions are extremely consistent across these diverse technical domains and could reasonably be expected to apply to broader chemical topics than fullerenes that span multiple structural classes. Finally, lessons learned about integrating the technical domain experts with the data mining tools are presented.

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

So Why Would a Pigeon Stand on One Leg (or Limp without Hurting)?

ERIC Educational Resources Information Center

Hrepic, Zdeslav

2012-01-01

While we still do not have a definitive answer about the reason(s) for which birds stand on one leg, a list of suggestions has been offered both by expert ornithologists and amateur birdwatchers. We offer a perspective grounded in statics and rotational dynamics that has not been suggested in the literature. The discussion has implications for…

A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

DOT National Transportation Integrated Search

1987-01-01

Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

Knowledge elicitation for an operator assistant system in process control tasks

NASA Technical Reports Server (NTRS)

Boy, Guy A.

1988-01-01

A knowledge based system (KBS) methodology designed to study human machine interactions and levels of autonomy in allocation of process control tasks is presented. Users are provided with operation manuals to assist them in normal and abnormal situations. Unfortunately, operation manuals usually represent only the functioning logic of the system to be controlled. The user logic is often totally different. A method is focused on which illicits user logic to refine a KBS shell called an Operator Assistant (OA). If the OA is to help the user, it is necessary to know what level of autonomy gives the optimal performance of the overall man-machine system. For example, for diagnoses that must be carried out carefully by both the user and the OA, interactions are frequent, and processing is mostly sequential. Other diagnoses can be automated, in which the case the OA must be able to explain its reasoning in an appropriate level of detail. OA structure was used to design a working KBS called HORSES (Human Orbital Refueling System Expert System). Protocol analysis of pilots interacting with this system reveals that the a-priori analytical knowledge becomes more structured with training and the situation patterns more complex and dynamic. This approach can improve the a-priori understanding of human and automatic reasoning.

PCLIPS: Parallel CLIPS

NASA Technical Reports Server (NTRS)

Gryphon, Coranth D.; Miller, Mark D.

1991-01-01

PCLIPS (Parallel CLIPS) is a set of extensions to the C Language Integrated Production System (CLIPS) expert system language. PCLIPS is intended to provide an environment for the development of more complex, extensive expert systems. Multiple CLIPS expert systems are now capable of running simultaneously on separate processors, or separate machines, thus dramatically increasing the scope of solvable tasks within the expert systems. As a tool for parallel processing, PCLIPS allows for an expert system to add to its fact-base information generated by other expert systems, thus allowing systems to assist each other in solving a complex problem. This allows individual expert systems to be more compact and efficient, and thus run faster or on smaller machines.

Applications of artificial intelligence to scientific research

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen

1986-01-01

Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

Healthcare holds on tight. As the markets roil and financial giants fall, experts say things won't be all that bad for healthcare organizations.

PubMed

Galloro, Vince

2008-09-22

Investor fear stirred up by the news last week about Lehman Bros. and AIG should eventually subside, leaving little long-term effect on healthcare finance, experts say. Chris Payne, left, with healthcare financial advisory firm Ponder & Co., says, "I don't see any fundamental reason why this will cause a lack of capital to healthcare organizations".

Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

Construction of a clinical decision support system for undergoing surgery based on domain ontology and rules reasoning.

PubMed

Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

2014-05-01

To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé-Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia.

A tool to enhance occupational therapy reasoning from ICF perspective: The Hasselt Occupational Performance Profile (H-OPP).

PubMed

Ghysels, R; Vanroye, E; Westhovens, M; Spooren, A

2017-03-01

In order to enhance occupational therapy reasoning in clinical practice, different elements such as client-centred approach, evidence-based care and interdisciplinary work should be taken into account, but is a challenge. To describe the development of the digital Hasselt Occupational Performance Profile (H-OPP © ) that enhances occupational therapy reasoning from ICF perspective. A participative qualitative design was used to create the H-OPP © in an iterative way in which occupational therapy lectures, ICF experts, students and occupational therapists in the field were involved. After linking occupational therapy terminology to the ICF, different stages of the H-OPP were identified and elaborated with main features: generating an occupational performance profile based on inventarization of problems and possibilities, formulating an occupational performance diagnosis and enabling to create an intervention plan. In all stages, both the perspectives of the client and the occupational therapist were taken into account. To increase practical use, the tool was further elaborated and digitalized. The H-OPP © is a digital coach that guides and facilitates professional reasoning in (novice) occupational therapists. It augments involvement of the client system. Furthermore, it enhances interdisciplinary communication and evidence-based care.

Integrated Systems Health Management for Intelligent Systems

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Melcher, Kevin

2011-01-01

The implementation of an integrated system health management (ISHM) capability is fundamentally linked to the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system. Management implies storage, distribution, sharing, maintenance, processing, reasoning, and presentation. ISHM is akin to having a team of experts who are all individually and collectively observing and analyzing a complex system, and communicating effectively with each other in order to arrive at an accurate and reliable assessment of its health. In this chapter, concepts, procedures, and approaches are presented as a foundation for implementing an ISHM capability relevant to intelligent systems. The capability stresses integration of DIaK from all elements of a system, emphasizing an advance toward an on-board, autonomous capability. Both ground-based and on-board ISHM capabilities are addressed. The information presented is the result of many years of research, development, and maturation of technologies, and of prototype implementations in operational systems.

Porting a Mental Expert System to a Mainstream Programming Environment

PubMed Central

Jao, Chiang S.; Hier, Daniel B.; Dollear, Winifred; Fu, Wenying

2001-01-01

Expert systems are increasingly being applied to problems in medical diagnosis and treatment. Initial medical expert systems were programmed in specialized “expert system” shell programming environments. As the power of mainstream programming languages has increased, it has become possible to implement medical expert systems within these mainstream languages. We originally implemented an expert system to record and score the mental status examination utilizing a specialized expert system programming environment. We have now ported that application to a mainstream programming environment without losing any functionality of an accurate and comprehensive diagnostic tool. New system supplements the need of normative consultation report and offline reference library to the traditional patient care system.

Sherlock Holmes: an expert's view of expertise.

PubMed

André, Didierjean; Fernand, Gobet

2008-02-01

In recent years, there has been an intense research effort to understand the cognitive processes and structures underlying expert behaviour. Work in different fields, including scientific domains, sports, games and mnemonics, has shown that there are vast differences in perceptual abilities between experts and novices, and that these differences may underpin other cognitive differences in learning, memory and problem solving. In this article, we evaluate the progress made in the last years through the eyes of an outstanding, albeit fictional, expert: Sherlock Holmes. We first use the Sherlock Holmes character to illustrate expert processes as described by current research and theories. In particular, the role of perception, as well as the nature and influence of expert knowledge, are all present in the description of Conan Doyle's hero. In the second part of the article, we discuss a number of issues that current research on expertise has barely addressed. These gaps include, for example, several forms of reasoning, the influence of emotions on cognition, and the effect of age on experts' knowledge and cognitive processes. Thus, although nearly 120-year-old, Conan Doyle's books show remarkable illustrations of expert behaviour, including the coverage of themes that have mostly been overlooked by current research.

Dual process theory and intermediate effect: are faculty and residents' performance on multiple-choice, licensing exam questions different?

PubMed

Dong, Ting; Durning, Steven J; Artino, Anthony R; van der Vleuten, Cees; Holmboe, Eric; Lipner, Rebecca; Schuwirth, Lambert

2015-04-01

Clinical reasoning is essential for the practice of medicine. Dual process theory conceptualizes reasoning as falling into two general categories: nonanalytic reasoning (pattern recognition) and analytic reasoning (active comparing and contrasting of alternatives). The debate continues regarding how expert performance develops and how individuals make the best use of analytic and nonanalytic processes. Several investigators have identified the unexpected finding that intermediates tend to perform better on licensing examination items than experts, which has been termed the "intermediate effect." We explored differences between faculty and residents on multiple-choice questions (MCQs) using dual process measures (both reading and answering times) to inform this ongoing debate. Faculty (board-certified internists; experts) and residents (internal medicine interns; intermediates) answered live licensing examination MCQs (U.S. Medical Licensing Examination Step 2 Clinical Knowledge and American Board of Internal Medicine Certifying Examination) while being timed. We conducted repeated analysis of variance to compare the 2 groups on average reading time, answering time, and accuracy on various types of items. Faculty and residents did not differ significantly in reading time [F (1,35) = 0.01, p = 0.93], answering time [F (1,35) = 0.60, p = 0.44], or accuracy [F (1,35) = 0.24, p = 0.63] regardless of easy or hard items. Dual process theory was not evidenced in this study. However, this lack of difference between faculty and residents may have been affected by the small sample size of participants and MCQs may not reflect how physicians made decisions in actual practice setting. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

MARBLE: A system for executing expert systems in parallel

NASA Technical Reports Server (NTRS)

Myers, Leonard; Johnson, Coe; Johnson, Dean

1990-01-01

This paper details the MARBLE 2.0 system which provides a parallel environment for cooperating expert systems. The work has been done in conjunction with the development of an intelligent computer-aided design system, ICADS, by the CAD Research Unit of the Design Institute at California Polytechnic State University. MARBLE (Multiple Accessed Rete Blackboard Linked Experts) is a system of C Language Production Systems (CLIPS) expert system tool. A copied blackboard is used for communication between the shells to establish an architecture which supports cooperating expert systems that execute in parallel. The design of MARBLE is simple, but it provides support for a rich variety of configurations, while making it relatively easy to demonstrate the correctness of its parallel execution features. In its most elementary configuration, individual CLIPS expert systems execute on their own processors and communicate with each other through a modified blackboard. Control of the system as a whole, and specifically of writing to the blackboard is provided by one of the CLIPS expert systems, an expert control system.

Processes in construction of failure management expert systems from device design information

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Lance, Nick

1987-01-01

This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.

Ask the experts how to treat individuals with spatial neglect: a survey study.

PubMed

Chen, Peii; Pitteri, Marco; Gillen, Glen; Ayyala, Harsha

2017-07-11

Spatial neglect (SN) impedes rehabilitation success and leaves long-term consequences. We asked experts to provide their opinions in addressing SN by scenario (ideal vs. reality) and by recovery phase (earliest, acute, subacute, and chronic). Experts were individuals who have assessed or treated patients with SN clinically. This study was conducted using an anonymous survey on the Internet with 189 responders over 3 months. Located in 23 different countries, 127 experts of seven disciplines were included (occupational therapy, physical therapy, nursing, speech and language pathology or therapy, neurology, physical medicine and rehabilitation, and psychology or neuropsychology). Comparing the two scenarios, more treatments were selected in the ideal than in the reality scenario for all recovery phases except for the chronic phase. In both scenarios, (1) more treatments were selected in acute and subacute phases than in earliest or chronic phases, (2) less experienced experts selected diverse treatment options more often, and (3) highly experienced experts were more likely to provide their reasons of treatment selection, suggestions of treatment delivery methods, and other insights. Finally, 83.7% reported obstacles in treating SN. Experts' treatment selections are consistent with current evidence and practice guidelines. Recognizing the limitation of evidence, their opinions may help generate ideas in various topics (e.g., dosing, integrative intervention, and treatment implementation) to be examined in future studies. Implications for Rehabilitation Clinicians with experience in treating people with spatial neglect (i.e., experts as defined in the present study) recognized the limitation of evidence but nonetheless suggested specific treatments by recovery phase. In both the reality and ideal scenarios, experts included visual scanning, active limb activation, and sustained attention training in the top-five selections. Prism adaptation was in the top-five selections in the ideal scenario, while in the reality scenario, it was in the top-five in all phases except for the earliest phase where it was the sixth most selected. They also shared their valuable opinions in when to use which treatment to address spatial neglect and how to deliver certain interventions, which may help to generate ideas in various topics (e.g., dosing, integrative intervention, knowledge dissemination, and treatment implementation) that can be examined in future studies. We suggest that (1) clinicians consider collective expert opinions reported here to enhance their clinical judgment and practices, (2) researchers develop studies focused on treatments with limited evidence but selected here by experts, and (3) funding agencies provide the means to research and implementation projects that will generate rich information for improving practice guidelines and rehabilitation outcomes for patients with spatial neglect. The majority of the experts reported some obstacles in providing treatment for spatial neglect, and time and equipment shortages were the most common barriers, which should be addressed at the system level to determine whether removing those barriers have long-term beneficial impacts on both patients and healthcare systems.

Chapter 1: Biomedical knowledge integration.

PubMed

Payne, Philip R O

2012-01-01

The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems.

Chapter 1: Biomedical Knowledge Integration

PubMed Central

Payne, Philip R. O.

2012-01-01

The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems. PMID:23300416

Testing expert systems

NASA Technical Reports Server (NTRS)

Chang, C. L.; Stachowitz, R. A.

1988-01-01

Software quality is of primary concern in all large-scale expert system development efforts. Building appropriate validation and test tools for ensuring software reliability of expert systems is therefore required. The Expert Systems Validation Associate (EVA) is a validation system under development at the Lockheed Artificial Intelligence Center. EVA provides a wide range of validation and test tools to check correctness, consistency, and completeness of an expert system. Testing a major function of EVA. It means executing an expert system with test cases with the intent of finding errors. In this paper, we describe many different types of testing such as function-based testing, structure-based testing, and data-based testing. We describe how appropriate test cases may be selected in order to perform good and thorough testing of an expert system.

Real Time Data System (RTDS)

NASA Technical Reports Server (NTRS)

Muratore, John F.

1991-01-01

Lessons learned from operational real time expert systems are examined. The basic system architecture is discussed. An expert system is any software that performs tasks to a standard that would normally require a human expert. An expert system implies knowledge contained in data rather than code. And an expert system implies the use of heuristics as well as algorithms. The 15 top lessons learned by the operation of a real time data system are presented.

Expert systems applications for space shuttle payload integration automation

NASA Technical Reports Server (NTRS)

Morris, Keith

1988-01-01

Expert systems technologies have been and are continuing to be applied to NASA's Space Shuttle orbiter payload integration problems to provide a level of automation previously unrealizable. NASA's Space Shuttle orbiter was designed to be extremely flexible in its ability to accommodate many different types and combinations of satellites and experiments (payloads) within its payload bay. This flexibility results in differnet and unique engineering resource requirements for each of its payloads, creating recurring payload and cargo integration problems. Expert systems provide a successful solution for these recurring problems. The Orbiter Payload Bay Cabling Expert (EXCABL) was the first expert system, developed to solve the electrical services provisioning problem. A second expert system, EXMATCH, was developed to generate a list of the reusable installation drawings available for each EXCABL solution. These successes have proved the applicability of expert systems technologies to payload integration problems and consequently a third expert system is currently in work. These three expert systems, the manner in which they resolve payload problems and how they will be integrated are described.

Integration of object-oriented knowledge representation with the CLIPS rule based system

NASA Technical Reports Server (NTRS)

Logie, David S.; Kamil, Hasan

1990-01-01

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

Diagnosing anomalies of spacecraft for space maintenance and servicing

NASA Astrophysics Data System (ADS)

Lauriente, Michael; Rolincik, Mark; Koons, Harry C.; Gorney, David

1994-01-01

Very often servicing of satellites is necessary to replace components which are responsible for anomalous behavior of satellite operations due to adverse interactions with the natural space environment. A major difficulty with this diagnosis is that those responsible for diagnosing these anomalies do not have the tools to assess the role of the space environment causing the anomaly. To address this issue, we have under development a new rule-based, expert system for diagnosing spacecraft anomalies. The knowledge base consists of over two-hundred rules and provides links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. When the user selects the novice mode, the system automatically gives detailed explanations and descriptions of terms and reasoning as the session progresses, in a sense teaching the user. As such it is an effective tutoring tool. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The system is available on-line and uses C Language Integrated Production System (CLIPS), an expert shell developed by the NASA Johnson Space Center AI Laboratory in Houston.

Hierarchical structure and importance of patients' reasons for treatment choices in knee and hip osteoarthritis: a concept mapping study.

PubMed

Selten, Ellen M H; Geenen, Rinie; van der Laan, Willemijn H; van der Meulen-Dilling, Roelien G; Schers, Henk J; Nijhof, Marc W; van den Ende, Cornelia H M; Vriezekolk, Johanna E

2017-02-01

To improve patients' use of conservative treatment options of hip and knee OA, in-depth understanding of reasons underlying patients' treatment choices is required. The current study adopted a concept mapping method to thematically structure and prioritize reasons for treatment choice in knee and hip OA from a patients' perspective. Multiple reasons for treatment choices were previously identified using in-depth interviews. In consensus meetings, experts derived 51 representative reasons from the interviews. Thirty-six patients individually sorted the 51 reasons in two card-sorting tasks: one based on content similarity, and one based on importance of reasons. The individual sortings of the first card-sorting task provided input for a hierarchical cluster analysis (squared Euclidian distances, Ward's method). The importance of the reasons and clusters were examined using descriptive statistics. The hierarchical structure of reasons for treatment choices showed a core distinction between two categories of clusters: barriers [subdivided into context (e.g. the healthcare system) and disadvantages] and outcome (subdivided into treatment and personal life). At the lowest level, 15 clusters were identified of which the clusters Physical functioning, Risks and Prosthesis were considered most important when making a treatment decision for hip or knee OA. Patients' treatment choices in knee and hip OA are guided by contextual barriers, disadvantages of the treatment, outcomes of the treatment and consequences for personal life. The structured overview of reasons can be used to support shared decision-making. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Intelligent methods for the process parameter determination of plastic injection molding

NASA Astrophysics Data System (ADS)

Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

2018-03-01

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

An Expert System Framework for Adaptive Evidential Reasoning: Application to In-Flight Route Re-Planning

DTIC Science & Technology

1986-03-21

i t a t i v e frameworks (e.g., Doyle, Toulmin , P . Cohen), and e f f o r t s t o syn thes i ze l o g i c and p r o b a b i l i t y (Nilsson...logic allows for provisional acceptance of uncer- tain premises, which may later be retracted when they lead to contradictory conclusions. Toulmin (1958...A1 researchers] have accepted without hesitation as impeccable." * The basic framework of an argument, according to Toulmin , is as follows ( Toulmin

Engineering monitoring expert system's developer

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1991-01-01

This research project is designed to apply artificial intelligence technology including expert systems, dynamic interface of neural networks, and hypertext to construct an expert system developer. The developer environment is specifically suited to building expert systems which monitor the performance of ground support equipment for propulsion systems and testing facilities. The expert system developer, through the use of a graphics interface and a rule network, will be transparent to the user during rule constructing and data scanning of the knowledge base. The project will result in a software system that allows its user to build specific monitoring type expert systems which monitor various equipments used for propulsion systems or ground testing facilities and accrues system performance information in a dynamic knowledge base.

Expert systems built by the Expert: An evaluation of OPS5

NASA Technical Reports Server (NTRS)

Jackson, Robert

1987-01-01

Two expert systems were written in OPS5 by the expert, a Ph.D. astronomer with no prior experience in artificial intelligence or expert systems, without the use of a knowledge engineer. The first system was built from scratch and uses 146 rules to check for duplication of scientific information within a pool of prospective observations. The second system was grafted onto another expert system and uses 149 additional rules to estimate the spacecraft and ground resources consumed by a set of prospective observations. The small vocabulary, the IF this occurs THEN do that logical structure of OPS5, and the ability to follow program execution allowed the expert to design and implement these systems with only the data structures and rules of another OPS5 system as an example. The modularity of the rules in OPS5 allowed the second system to modify the rulebase of the system onto which it was grafted without changing the code or the operation of that system. These experiences show that experts are able to develop their own expert systems due to the ease of programming and code reusability in OPS5.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

Artificial intelligence and space power systems automation

NASA Technical Reports Server (NTRS)

Weeks, David J.

1987-01-01

Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

Mapping the level of scientific reasoning skills to instructional methodologies among Malaysian science-mathematics-engineering undergraduates

NASA Astrophysics Data System (ADS)

Tajudin, Nor'ain Mohd.; Saad, Noor Shah; Rahman, Nurulhuda Abd; Yahaya, Asmayati; Alimon, Hasimah; Dollah, Mohd. Uzi; Abd Karim, Mohd. Mustaman

2012-05-01

The objectives of this quantitative survey research were (1) to establish the level of scientific reasoning (SR) skills among science, mathematics and engineering (SME) undergraduates in Malaysian Institute of Higher Learning (IHL); (b) to identify the types of instructional methods in teaching SME at universities; and (c) to map instructional methods employed to the level of SR skills among the undergraduates. There were six universities according to zone involved in this study using the stratification random sampling technique. For each university, the faculties that involved were faculties which have degree students in science, mathematics and engineering programme. A total of 975 students were participated in this study. There were two instruments used in this study namely, the Lawson Scientific Reasoning Skills Test and the Lecturers' Teaching Style Survey. The descriptive statistics and the inferential statistics such as mean, t-test and Pearson correlation were used to analyze the data. Findings of the study showed that most students had concrete level of scientific reasoning skills where the overall mean was 3.23. The expert and delegator were dominant lecturers' teaching styles according to students' perception. In addition, there was no correlation between lecturers' teaching style and the level of scientific reasoning skills. Thus, this study cannot map the dominant lecturers' teaching style to the level of scientific reasoning skills of Science, Mathematics and Engineering undergraduates in Malaysian Public Institute of Higher Learning. Nevertheless, this study gave some indications that the expert and delegator teaching styles were not contributed to the development of students' scientific reasoning skills. This study can be used as a baseline for Science, Mathematics and Engineering undergraduates' level of scientific reasoning skills in Malaysian Public Institute of Higher Learning. Overall, this study also opens an endless source of other researchers to investigate more areas on scientific reasoning skills so that the potential instructional model can be developed to enhance students' level of scientific reasoning skills in Malaysian Public Institute of Higher Learning.

Considerations in development of expert systems for real-time space applications

NASA Technical Reports Server (NTRS)

Murugesan, S.

1988-01-01

Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications.

Bayesian versus politically motivated reasoning in human perception of climate anomalies

NASA Astrophysics Data System (ADS)

Ripberger, Joseph T.; Jenkins-Smith, Hank C.; Silva, Carol L.; Carlson, Deven E.; Gupta, Kuhika; Carlson, Nina; Dunlap, Riley E.

2017-11-01

In complex systems where humans and nature interact to produce joint outcomes, mitigation, adaptation, and resilience require that humans perceive feedback—signals of health and distress—from natural systems. In many instances, humans readily perceive feedback. In others, feedback is more difficult to perceive, so humans rely on experts, heuristics, biases, and/or identify confirming rationalities that may distort perceptions of feedback. This study explores human perception of feedback from natural systems by testing alternate conceptions about how individuals perceive climate anomalies, a form of feedback from the climate system. Results indicate that individuals generally perceive climate anomalies, especially when the anomalies are relatively extreme and persistent. Moreover, this finding is largely robust to political differences that generate predictable but small biases in feedback perception at extreme ends of the partisan spectrum. The subtlety of these biases bodes well for mitigation, adaptation, and resilience as human systems continue to interact with a changing climate system.

Northeast Artificial Intelligence Consortium annual report. Volume 2. 1988. Discussing, using, and recognizing plans (NLP). Interim report, January-December 1988

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shapiro, S.C.; Woolf, B.

The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and the Office of Scientific Research. Its purpose is to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress that has been made in the fourth year of the existence of the NAIC on the technical research tasks undertaken at the member universities. The topics covered in general are: versatile expert system for equipment maintenance, distributed AI for communications system control, automatic photointerpretation, time-oriented problem solving, speech understanding systems, knowledge base maintenance, hardwaremore » architectures for very large systems, knowledge-based reasoning and planning, and a knowledge acquisition, assistance, and explanation system. The specific topic for this volume is the recognition of plans expressed in natural language, followed by their discussion and use.« less

Class Model Development Using Business Rules

NASA Astrophysics Data System (ADS)

Skersys, Tomas; Gudas, Saulius

New developments in the area of computer-aided system engineering (CASE) greatly improve processes of the information systems development life cycle (ISDLC). Much effort is put into the quality improvement issues, but IS development projects still suffer from the poor quality of models during the system analysis and design cycles. At some degree, quality of models that are developed using CASE tools can be assured using various. automated. model comparison, syntax. checking procedures. It. is also reasonable to check these models against the business domain knowledge, but the domain knowledge stored in the repository of CASE tool (enterprise model) is insufficient (Gudas et al. 2004). Involvement of business domain experts into these processes is complicated because non- IT people often find it difficult to understand models that were developed by IT professionals using some specific modeling language.

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

BREAST: a novel method to improve the diagnostic efficacy of mammography

NASA Astrophysics Data System (ADS)

Brennan, P. C.; Tapia, K.; Ryan, J.; Lee, W.

2013-03-01

High quality breast imaging and accurate image assessment are critical to the early diagnoses, treatment and management of women with breast cancer. Breast Screen Reader Assessment Strategy (BREAST) provides a platform, accessible by researchers and clinicians world-wide, which will contain image data bases, algorithms to assess reader performance and on-line systems for image evaluation. The platform will contribute to the diagnostic efficacy of breast imaging in Australia and beyond on two fronts: reducing errors in mammography, and transforming our assessment of novel technologies and techniques. Mammography is the primary diagnostic tool for detecting breast cancer with over 800,000 women X-rayed each year in Australia, however, it fails to detect 30% of breast cancers with a number of missed cancers being visible on the image [1-6]. BREAST will monitor the mistakes, identify reasons for mammographic errors, and facilitate innovative solutions to reduce error rates. The BREAST platform has the potential to enable expert assessment of breast imaging innovations, anywhere in the world where experts or innovations are located. Currently, innovations are often being assessed by limited numbers of individuals who happen to be geographically located close to the innovation, resulting in equivocal studies with low statistical power. BREAST will transform this current paradigm by enabling large numbers of experts to assess any new method or technology using our embedded evaluation methods. We are confident that this world-first system will play an important part in the future efficacy of breast imaging.

Unpacking Exoplanet Detection Using Pedagogical Discipline Representations (PDRs)

NASA Astrophysics Data System (ADS)

Prather, Edward E.; Chambers, Timothy G.; Wallace, Colin Scott; Brissenden, Gina

2017-01-01

Successful educators know the importance of using multiple representations to teach the content of their disciplines. We have all seen the moments of epiphany that can be inspired when engaging with just the right representation of a difficult concept. The formal study of the cognitive impact of different representations on learners is now an active area of education research. The affordances of a particular representation are defined as the elements of disciplinary knowledge that students are able to access and reason about using that representation. Instructors with expert pedagogical content knowledge teach each topic using representations with complementary affordances, maximizing their students’ opportunity to develop fluency with all aspects of the topic. The work presented here examines how we have applied the theory of affordances to the development of pedagogical discipline representation (PDR) in an effort to provide access to, and help non-science-majors engage in expert-like reasoning about, general relativity as applied to detection of exoplanets. We define a pedagogical discipline representation (PDR) as a representation that has been uniquely tailored for the purpose of teaching a specific topic within a discipline. PDRs can be simplified versions of expert representations or can be highly contextualized with features that purposefully help unpack specific reasoning or concepts, and engage learners’ pre-existing mental models while promoting and enabling critical discourse. Examples of PDRs used for instruction and assessment will be provided along with preliminary results documenting the effectiveness of their use in the classroom.

An hierarchical approach to performance evaluation of expert systems

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Kavi, Srinu

1985-01-01

The number and size of expert systems is growing rapidly. Formal evaluation of these systems - which is not performed for many systems - increases the acceptability by the user community and hence their success. Hierarchical evaluation that had been conducted for computer systems is applied for expert system performance evaluation. Expert systems are also evaluated by treating them as software systems (or programs). This paper reports many of the basic concepts and ideas in the Performance Evaluation of Expert Systems Study being conducted at the University of Southwestern Louisiana.

An engineering approach to the use of expert systems technology in avionics applications

NASA Technical Reports Server (NTRS)

Duke, E. L.; Regenie, V. A.; Brazee, M.; Brumbaugh, R. W.

1986-01-01

The concept of using a knowledge compiler to transform the knowledge base and inference mechanism of an expert system into a conventional program is presented. The need to accommodate real-time systems requirements in applications such as embedded avionics is outlined. Expert systems and a brief comparison of expert systems and conventional programs are reviewed. Avionics applications of expert systems are discussed before the discussions of applying the proposed concept to example systems using forward and backward chaining.

Expert systems for real-time monitoring and fault diagnosis

NASA Technical Reports Server (NTRS)

Edwards, S. J.; Caglayan, A. K.

1989-01-01

Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft.

Equating an expert system to a classifier in order to evaluate the expert system

NASA Technical Reports Server (NTRS)

Odell, Patrick L.

1989-01-01

A strategy to evaluate an expert system is formulated. The strategy proposed is based on finding an equivalent classifier to an expert system and evaluate that classifier with respect to an optimal classifier, a Bayes classifier. Here it is shown that for the rules considered an equivalent classifier exists. Also, a brief consideration of meta and meta-meta rules is included. Also, a taxonomy of expert systems is presented and an assertion made that an equivalent classifier exists for each type of expert system in the taxonomy with associated sets of underlying assumptions.

Three CLIPS-based expert systems for solving engineering problems

NASA Technical Reports Server (NTRS)

Parkinson, W. J.; Luger, G. F.; Bretz, R. E.

1990-01-01

We have written three expert systems, using the CLIPS PC-based expert system shell. These three expert systems are rule based and are relatively small, with the largest containing slightly less than 200 rules. The first expert system is an expert assistant that was written to help users of the ASPEN computer code choose the proper thermodynamic package to use with their particular vapor-liquid equilibrium problem. The second expert system was designed to help petroleum engineers choose the proper enhanced oil recovery method to be used with a given reservoir. The effectiveness of each technique is highly dependent upon the reservoir conditions. The third expert system is a combination consultant and control system. This system was designed specifically for silicon carbide whisker growth. Silicon carbide whiskers are an extremely strong product used to make ceramic and metal composites. The manufacture of whiskers is a very complicated process. which to date. has defied a good mathematical model. The process was run by experts who had gained their expertise by trial and error. A system of rules was devised by these experts both for procedure setup and for the process control. In this paper we discuss the three problem areas of the design, development and evaluation of the CLIPS-based programs.

Small Knowledge-Based Systems in Education and Training: Something New Under the Sun.

ERIC Educational Resources Information Center

Wilson, Brent G.; Welsh, Jack R.

1986-01-01

Discusses artificial intelligence, robotics, natural language processing, and expert or knowledge-based systems research; examines two large expert systems, MYCIN and XCON; and reviews the resources required to build large expert systems and affordable smaller systems (intelligent job aids) for training. Expert system vendors and products are…

Concept Maps for Improved Science Reasoning and Writing: Complexity Isn’t Everything

PubMed Central

Dowd, Jason E.; Duncan, Tanya; Reynolds, Julie A.

2015-01-01

A pervasive notion in the literature is that complex concept maps reflect greater knowledge and/or more expert-like thinking than less complex concept maps. We show that concept maps used to structure scientific writing and clarify scientific reasoning do not adhere to this notion. In an undergraduate course for thesis writers, students use concept maps instead of traditional outlines to define the boundaries and scope of their research and to construct an argument for the significance of their research. Students generate maps at the beginning of the semester, revise after peer review, and revise once more at the end of the semester. Although some students revised their maps to make them more complex, a significant proportion of students simplified their maps. We found no correlation between increased complexity and improved scientific reasoning and writing skills, suggesting that sometimes students simplify their understanding as they develop more expert-like thinking. These results suggest that concept maps, when used as an intervention, can meet the varying needs of a diverse population of student writers. PMID:26538388

Expert systems for C3I. Volume 1. A user's introduction

NASA Astrophysics Data System (ADS)

Clapp, J. A.; Hockett, S. M.; Prelle, M. J.; Tallant, A. M.; Triant, D. D.

1985-10-01

There has been a tremendous burgeoning of interest in artificial intelligence (AI) over the last few years. Investments of commercial and government sponsors reflect a widespread belief that AI is now ready for practical applications. The area of AI currently receiving the greatest attention and investment is expert system technology. Most major high tech corporations have begun to develop expert systems, and many software houses specializing in expert system tools and applications have recently appeared. The defense community is one of the heaviest investors in expert system technology, and within this community one of the application areas receiving greatest attention is C3I. Many ESD programs are now beginning to ask whether expert system applications for C3I are ready for incorporation into ESD-developed systems, and, if so, what are the potential benefits and risks of doing so. This report was prepared to help ESD and MITRE personnel working on acquisition programs to address these issues and to gain a better understanding of what expert systems are all about. The primary intention of this report is to investigate what expert systems are and the advances that are being made in expert system technology for C3I applications. The report begins with a brief tutorial on expert systems, emphasizing how they differ from conventional software systems and what they are best at doing.

Interfaces and Expert Systems for Online Retrieval.

ERIC Educational Resources Information Center

Kehoe, Cynthia A.

1985-01-01

This paper reviews the history of separate online system interfaces which led to efforts to develop expert systems for searching databases, particularly for end users, and introduces the research on such expert systems. Appended is a bibliography of sources on interfaces and expert systems for online retrieval. (Author/EJS)

Clinical reasoning and its application to nursing: concepts and research studies.

PubMed

Banning, Maggi

2008-05-01

Clinical reasoning may be defined as "the process of applying knowledge and expertise to a clinical situation to develop a solution" [Carr, S., 2004. A framework for understanding clinical reasoning in community nursing. J. Clin. Nursing 13 (7), 850-857]. Several forms of reasoning exist each has its own merits and uses. Reasoning involves the processes of cognition or thinking and metacognition. In nursing, clinical reasoning skills are an expected component of expert and competent practise. Nurse research studies have identified concepts, processes and thinking strategies that might underpin the clinical reasoning used by pre-registration nurses and experienced nurses. Much of the available research on reasoning is based on the use of the think aloud approach. Although this is a useful method, it is dependent on ability to describe and verbalise the reasoning process. More nursing research is needed to explore the clinical reasoning process. Investment in teaching and learning methods is needed to enhance clinical reasoning skills in nurses.

Wisdom in clinical reasoning and medical practice.

PubMed

Edmondson, Ricca; Pearce, Jane; Woerner, Markus H

2009-01-01

Exploring informal components of clinical reasoning, we argue that they need to be understood via the analysis of professional wisdom. Wise decisions are needed where action or insight is vital, but neither everyday nor expert knowledge provides solutions. Wisdom combines experiential, intellectual, ethical, emotional and practical capacities; we contend that it is also more strongly social than is usually appreciated. But many accounts of reasoning specifically rule out such features as irrational. Seeking to illuminate how wisdom operates, we therefore build on Aristotle's work on informal reasoning. His account of rhetorical communication shows how non-formal components can play active parts in reasoning, retaining, or even enhancing its reasonableness. We extend this account, applying it to forms of healthcare-related reasoning which are characterised by the need for wise decision-making. We then go on to explore some of what clinical wise reasoning may mean, concluding with a case taken from psychotherapeutic practice.

The motion behind the symbols: a vital role for dynamism in the conceptualization of limits and continuity in expert mathematics.

PubMed

Marghetis, Tyler; Núñez, Rafael

2013-04-01

The canonical history of mathematics suggests that the late 19th-century "arithmetization" of calculus marked a shift away from spatial-dynamic intuitions, grounding concepts in static, rigorous definitions. Instead, we argue that mathematicians, both historically and currently, rely on dynamic conceptualizations of mathematical concepts like continuity, limits, and functions. In this article, we present two studies of the role of dynamic conceptual systems in expert proof. The first is an analysis of co-speech gesture produced by mathematics graduate students while proving a theorem, which reveals a reliance on dynamic conceptual resources. The second is a cognitive-historical case study of an incident in 19th-century mathematics that suggests a functional role for such dynamism in the reasoning of the renowned mathematician Augustin Cauchy. Taken together, these two studies indicate that essential concepts in calculus that have been defined entirely in abstract, static terms are nevertheless conceptualized dynamically, in both contemporary and historical practice. Copyright © 2013 Cognitive Science Society, Inc.

A Distributed Artificial Intelligence Approach To Object Identification And Classification

NASA Astrophysics Data System (ADS)

Sikka, Digvijay I.; Varshney, Pramod K.; Vannicola, Vincent C.

1989-09-01

This paper presents an application of Distributed Artificial Intelligence (DAI) tools to the data fusion and classification problem. Our approach is to use a blackboard for information management and hypothe-ses formulation. The blackboard is used by the knowledge sources (KSs) for sharing information and posting their hypotheses on, just as experts sitting around a round table would do. The present simulation performs classification of an Aircraft(AC), after identifying it by its features, into disjoint sets (object classes) comprising of the five commercial ACs; Boeing 747, Boeing 707, DC10, Concord and Boeing 727. A situation data base is characterized by experimental data available from the three levels of expert reasoning. Ohio State University ElectroScience Laboratory provided this experimental data. To validate the architecture presented, we employ two KSs for modeling the sensors, aspect angle polarization feature and the ellipticity data. The system has been implemented on Symbolics 3645, under Genera 7.1, in Common LISP.

Expert and Knowledge Based Systems.

ERIC Educational Resources Information Center

Demaid, Adrian; Edwards, Lyndon

1987-01-01

Discusses the nature and current state of knowledge-based systems and expert systems. Describes an expert system from the viewpoints of a computer programmer and an applications expert. Addresses concerns related to materials selection and forecasts future developments in the teaching of materials engineering. (ML)

From expert to novice: an exploration of the experiences of new academic staff to a department of adult nursing studies.

PubMed

McArthur-Rouse, Fiona J

2008-05-01

This study explores the experiences of new academic staff to ascertain what they found difficult about adapting to their new roles and to evaluate the effectiveness of the mentorship system in addressing these difficulties. A semi-structured interview approach was used focusing on prior experiences and reasons for applying for their new post; formal induction and mentorship systems; and main concerns on commencing the new role. All academic staff employed in the department for less than two years were invited to participate with the exception of the researcher's own mentee; six out of seven agreed. The interviews were audio-taped and subjected to thematic analysis. Key themes included a lack of understanding regarding the functioning of the organization and a lack of clarity about the new role and their effectiveness in undertaking it. Participants identified a need for more practical guidance regarding the functional aspects of teaching. Although, they reported positive mentoring experiences these were variable. The study concludes that the transition from expert practitioner to novice lecturer can be problematic. Recommendations for facilitating the process include the introduction of a more robust mentoring system, specific preparation for the mentors, and the development of a positive departmental learning culture.

A Flight Expert System (FLES) For On-Board Fault Monitoring And Diagnosis

NASA Astrophysics Data System (ADS)

Ali, M.; Scharnhorst, D...; Ai, C. S.; Ferber, H. J.

1986-03-01

The increasing complexity of modern aircraft creates a need for a larger number of caution and warning devices. But more alerts require more memorization and higher work loads for the pilot and tend to induce a higher probability of errors. Therefore, we have developed an architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing and recovering from in-flight faults. A prototype of FLES has been implemented. A sensor simulation model was developed and employed to provide FLES with the airplane status information during the diagnostic process. The simulator is based partly on the Lockheed Advanced Concept System (ACS), a future generation airplane, and partly on the Boeing 737, an existing airplane. A distinction between two types of faults, maladjustments and malfunctions, has led us to take two approaches to fault diagnosis. These approaches are evident in two FLES subsystems: the flight phase monitor and the sensor interrupt handler. The specific problem addressed in these subsystems has been that of integrating information received from multiple sensors with domain knowledge in order to assess abnormal situations during airplane flight. This paper describes our reasons for handling malfunctions and maladjustments separately and the use of domain knowledge in the diagnosis of each.

A flight expert system (FLES) for on-board fault monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Ali, M.; Scharnhorst, D. A.; Ai, C. S.; Ferber, H. J.

1986-01-01

The increasing complexity of modern aircraft creates a need for a larger number of caution and warning devices. But more alerts require more memorization and higher work loads for the pilot and tend to induce a higher probability of errors. Therefore, an architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing and recovering from in-flight faults has been developed. A prototype of FLES has been implemented. A sensor simulation model was developed and employed to provide FLES with the airplane status information during the diagnostic process. The simulator is based partly on the Lockheed Advanced Concept System (ACS), a future generation airplane, and partly on the Boeing 737, an existing airplane. A distinction between two types of faults, maladjustments and malfunctions, has led us to take two approaches to fault diagnosis. These approaches are evident in two FLES subsystems: the flight phase monitor and the sensor interrupt handler. The specific problem addressed in these subsystems has been that of integrating information received from multiple sensors with domain knowledge in order to assess abnormal situations during airplane flight. This paper describes the reasons for handling malfunctions and maladjustments separately and the use of domain knowledge in the diagnosis of each.

Measurement of prosocial reasoning among Chinese adolescents.

PubMed

Lai, Frank H Y; Siu, Andrew M H; Chan, Chewtyn C H; Shek, Daniel T L

2012-01-01

This study attempted to develop a standardized instrument for assessment of prosocial reasoning in Chinese populations. The Prosocial Reasoning Objective Measure (PROM) was translated, and a two-stage study was conducted to evaluate the psychometric properties of the translated instrument. The content validity, cultural relevance, and reading level of the translated instrument were evaluated by an expert panel. Upon revisions according to the expert opinions, the Chinese PROM demonstrated good content validity, "good-to-very good test-retest" reliability, and internal consistency. However, only partial support to the convergent validity of the Chinese PROM was found. In the first stage of the study (n = 50), the PROM scores had high positive correlations with empathy and negative correlations with personal distress and fantasy. These results were consistent with theoretical expectations, although this is also a concern that empathy had a close-to-unity correlation with PROM score in the small sample study of stage 1. In the second stage of the study (n = 566), the relationship between PROM scores and prosocial behavior appeared to be weak. Results suggest that there were many personal, family, or social factors that were linked to prosocial behavior, and prosocial reasoning might only contribute to a small proportion of variation in prosocial behavior among adolescents.

Measurement of Prosocial Reasoning among Chinese Adolescents

PubMed Central

Lai, Frank H. Y.; Siu, Andrew M. H.; Chan, Chewtyn C. H.; Shek, Daniel T. L.

2012-01-01

This study attempted to develop a standardized instrument for assessment of prosocial reasoning in Chinese populations. The Prosocial Reasoning Objective Measure (PROM) was translated, and a two-stage study was conducted to evaluate the psychometric properties of the translated instrument. The content validity, cultural relevance, and reading level of the translated instrument were evaluated by an expert panel. Upon revisions according to the expert opinions, the Chinese PROM demonstrated good content validity, “good-to-very good test-retest” reliability, and internal consistency. However, only partial support to the convergent validity of the Chinese PROM was found. In the first stage of the study (n = 50), the PROM scores had high positive correlations with empathy and negative correlations with personal distress and fantasy. These results were consistent with theoretical expectations, although this is also a concern that empathy had a close-to-unity correlation with PROM score in the small sample study of stage 1. In the second stage of the study (n = 566), the relationship between PROM scores and prosocial behavior appeared to be weak. Results suggest that there were many personal, family, or social factors that were linked to prosocial behavior, and prosocial reasoning might only contribute to a small proportion of variation in prosocial behavior among adolescents. PMID:22919293

Reliability and performance evaluation of systems containing embedded rule-based expert systems

NASA Technical Reports Server (NTRS)

Beaton, Robert M.; Adams, Milton B.; Harrison, James V. A.

1989-01-01

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Executing CLIPS expert systems in a distributed environment

NASA Technical Reports Server (NTRS)

Taylor, James; Myers, Leonard

1990-01-01

This paper describes a framework for running cooperating agents in a distributed environment to support the Intelligent Computer Aided Design System (ICADS), a project in progress at the CAD Research Unit of the Design Institute at the California Polytechnic State University. Currently, the systems aids an architectural designer in creating a floor plan that satisfies some general architectural constraints and project specific requirements. At the core of ICADS is the Blackboard Control System. Connected to the blackboard are any number of domain experts called Intelligent Design Tools (IDT). The Blackboard Control System monitors the evolving design as it is being drawn and helps resolve conflicts from the domain experts. The user serves as a partner in this system by manipulating the floor plan in the CAD system and validating recommendations made by the domain experts. The primary components of the Blackboard Control System are two expert systems executed by a modified CLIPS shell. The first is the Message Handler. The second is the Conflict Resolver. The Conflict Resolver synthesizes the suggestions made by the domain experts, which can be either CLIPS expert systems, or compiled C programs. In DEMO1, the current ICADS prototype, the CLIPS domain expert systems are Acoustics, Lighting, Structural, and Thermal; the compiled C domain experts are the CAD system and the User Interface.

Expert system prototype developments for NASA-KSC business and engineering applications

NASA Technical Reports Server (NTRS)

Ragusa, James M.; Gonzalez, Avelino J.

1988-01-01

Prototype expert systems developed for a variety of NASA projects in the business/management and engineering domains are discussed. Business-related problems addressed include an assistant for simulating launch vehicle processing, a plan advisor for the acquisition of automated data processing equipment, and an expert system for the identification of customer requirements. Engineering problems treated include an expert system for detecting potential ignition sources in LOX and gaseous-oxygen transportation systems and an expert system for hazardous-gas detection.

A CLIPS expert system for maximizing alfalfa (Medicago Sativa L.) production

NASA Technical Reports Server (NTRS)

Engel, B. A.; Jones, D. D.; Rhykerd, R. L.; Rhykerd, L. M.; Rhykerd, C. L., Jr.; Rhykerd, C. L.

1990-01-01

An alfalfa management expert system originally developed by Purdue University agricultural scientists on the PC Plus expert system shell from Texas Instrument has been updated and successfully converted to CLIPS (C Language Integrated Production System). This reduces the cost and legal restrictions associated with making the expert system available to agribusiness industries, extension personnel and farm managers and operators. The expert system includes recommendations concerning soil drainage, liming, P and K fertilization, weed control, variety selection and seeding rate including pure live seeds.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI).

PubMed

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non-expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI's robustness and sensitivity in capturing useful data relating to the students' conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. © 2016 T. Deane et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Skierarchy: Extending the Power of Crowdsourcing Using a Hierarchy of Domain Experts, Crowd and Machine Learning

DTIC Science & Technology

2012-11-01

college background and good reading comprehension skills in English, and bring to them to the office space to work for us full-time on micro-tasks. This...reasonable reading comprehension skills in English. The expert spent only 1/3rd the time as each member of the crowd in the entire annotation process...3. DATES COVERED 00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Skierarchy: Extending the Power of Crowdsourcing Using a Hierarchy of Domain

How to control if even experts are not sure: Robust fuzzy control

NASA Technical Reports Server (NTRS)

Nguyen, Hung T.; Kreinovich, Vladik YA.; Lea, Robert; Tolbert, Dana

1992-01-01

In real life, the degrees of certainty that correspond to one of the same expert can differ drastically, and fuzzy control algorithms translate these different degrees of uncertainty into different control strategies. In such situations, it is reasonable to choose a fuzzy control methodology that is the least vulnerable to this kind of uncertainty. It is shown that this 'robustness' demand leads to min and max for &- and V-operations, to 1-x for negation, and to centroid as a defuzzification procedure.

Knowledge-based fault diagnosis system for refuse collection vehicle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, CheeFai; Juffrizal, K.; Khalil, S. N.

The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledgemore » that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.« less

Using functional neuroimaging combined with a think-aloud protocol to explore clinical reasoning expertise in internal medicine.

PubMed

Durning, Steven J; Graner, John; Artino, Anthony R; Pangaro, Louis N; Beckman, Thomas; Holmboe, Eric; Oakes, Terrance; Roy, Michael; Riedy, Gerard; Capaldi, Vincent; Walter, Robert; van der Vleuten, Cees; Schuwirth, Lambert

2012-09-01

Clinical reasoning is essential to medical practice, but because it entails internal mental processes, it is difficult to assess. Functional magnetic resonance imaging (fMRI) and think-aloud protocols may improve understanding of clinical reasoning as these methods can more directly assess these processes. The objective of our study was to use a combination of fMRI and think-aloud procedures to examine fMRI correlates of a leading theoretical model in clinical reasoning based on experimental findings to date: analytic (i.e., actively comparing and contrasting diagnostic entities) and nonanalytic (i.e., pattern recognition) reasoning. We hypothesized that there would be functional neuroimaging differences between analytic and nonanalytic reasoning theory. 17 board-certified experts in internal medicine answered and reflected on validated U.S. Medical Licensing Exam and American Board of Internal Medicine multiple-choice questions (easy and difficult) during an fMRI scan. This procedure was followed by completion of a formal think-aloud procedure. fMRI findings provide some support for the presence of analytic and nonanalytic reasoning systems. Statistically significant activation of prefrontal cortex distinguished answering incorrectly versus correctly (p < 0.01), whereas activation of precuneus and midtemporal gyrus distinguished not guessing from guessing (p < 0.01). We found limited fMRI evidence to support analytic and nonanalytic reasoning theory, as our results indicate functional differences with correct vs. incorrect answers and guessing vs. not guessing. However, our findings did not suggest one consistent fMRI activation pattern of internal medicine expertise. This model of employing fMRI correlates offers opportunities to enhance our understanding of theory, as well as improve our teaching and assessment of clinical reasoning, a key outcome of medical education.

Developing expertise in surgery.

PubMed

Alderson, David

2010-01-01

The concept of expertise is widely embraced but poorly defined in surgery. Dictionary definitions differentiate between authority and experience, while a third view sees expertise as a mind-set rather than a status. Both absolute and relative models of expertise have been developed, and each allows a richer understanding of the application of these concepts to emerge. Trainees must develop both independent and interdependent expertise, and an appreciation of the essentially constructivist and uncertain nature of medical knowledge. Approach may be more important than innate talent; the concepts of 'flow', sustained 'deliberate practice' and 'adaptive expertise' are examples of expert approaches to learning. Non-analytical reasoning plays a key role in decision making at expert levels of practice. A technically gifted surgeon may be seen as a safety hazard rather than an expert if inter-dependent expertise has not been developed. Key roles of a surgical educator are to facilitate the development of an expert approach to education and to enable entry into and movement towards the centre of an expert community of practice.

Generative mechanistic explanation building in undergraduate molecular and cellular biology

NASA Astrophysics Data System (ADS)

Southard, Katelyn M.; Espindola, Melissa R.; Zaepfel, Samantha D.; Bolger, Molly S.

2017-09-01

When conducting scientific research, experts in molecular and cellular biology (MCB) use specific reasoning strategies to construct mechanistic explanations for the underlying causal features of molecular phenomena. We explored how undergraduate students applied this scientific practice in MCB. Drawing from studies of explanation building among scientists, we created and applied a theoretical framework to explore the strategies students use to construct explanations for 'novel' biological phenomena. Specifically, we explored how students navigated the multi-level nature of complex biological systems using generative mechanistic reasoning. Interviews were conducted with introductory and upper-division biology students at a large public university in the United States. Results of qualitative coding revealed key features of students' explanation building. Students used modular thinking to consider the functional subdivisions of the system, which they 'filled in' to varying degrees with mechanistic elements. They also hypothesised the involvement of mechanistic entities and instantiated abstract schema to adapt their explanations to unfamiliar biological contexts. Finally, we explored the flexible thinking that students used to hypothesise the impact of mutations on multi-leveled biological systems. Results revealed a number of ways that students drew mechanistic connections between molecules, functional modules (sets of molecules with an emergent function), cells, tissues, organisms and populations.

Heart health risk assessment system: a nonintrusive proposal using ontologies and expert rules.

PubMed

Garcia-Valverde, Teresa; Muñoz, Andrés; Arcas, Francisco; Bueno-Crespo, Andrés; Caballero, Alberto

2014-01-01

According to the World Health Organization, the world's leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc.) and her current activity (level of intensity, heart rate recommended for that activity, etc.). With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch.

Data Mining for Anomaly Detection

NASA Technical Reports Server (NTRS)

Biswas, Gautam; Mack, Daniel; Mylaraswamy, Dinkar; Bharadwaj, Raj

2013-01-01

The Vehicle Integrated Prognostics Reasoner (VIPR) program describes methods for enhanced diagnostics as well as a prognostic extension to current state of art Aircraft Diagnostic and Maintenance System (ADMS). VIPR introduced a new anomaly detection function for discovering previously undetected and undocumented situations, where there are clear deviations from nominal behavior. Once a baseline (nominal model of operations) is established, the detection and analysis is split between on-aircraft outlier generation and off-aircraft expert analysis to characterize and classify events that may not have been anticipated by individual system providers. Offline expert analysis is supported by data curation and data mining algorithms that can be applied in the contexts of supervised learning methods and unsupervised learning. In this report, we discuss efficient methods to implement the Kolmogorov complexity measure using compression algorithms, and run a systematic empirical analysis to determine the best compression measure. Our experiments established that the combination of the DZIP compression algorithm and CiDM distance measure provides the best results for capturing relevant properties of time series data encountered in aircraft operations. This combination was used as the basis for developing an unsupervised learning algorithm to define "nominal" flight segments using historical flight segments.

Heart Health Risk Assessment System: A Nonintrusive Proposal Using Ontologies and Expert Rules

PubMed Central

2014-01-01

According to the World Health Organization, the world's leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc.) and her current activity (level of intensity, heart rate recommended for that activity, etc.). With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch. PMID:25045715

Knowledge-acquisition tools for medical knowledge-based systems.

PubMed

Lanzola, G; Quaglini, S; Stefanelli, M

1995-03-01

Knowledge-based systems (KBS) have been proposed to solve a large variety of medical problems. A strategic issue for KBS development and maintenance are the efforts required for both knowledge engineers and domain experts. The proposed solution is building efficient knowledge acquisition (KA) tools. This paper presents a set of KA tools we are developing within a European Project called GAMES II. They have been designed after the formulation of an epistemological model of medical reasoning. The main goal is that of developing a computational framework which allows knowledge engineers and domain experts to interact cooperatively in developing a medical KBS. To this aim, a set of reusable software components is highly recommended. Their design was facilitated by the development of a methodology for KBS construction. It views this process as comprising two activities: the tailoring of the epistemological model to the specific medical task to be executed and the subsequent translation of this model into a computational architecture so that the connections between computational structures and their knowledge level counterparts are maintained. The KA tools we developed are illustrated taking examples from the behavior of a KBS we are building for the management of children with acute myeloid leukemia.

Does expert opinion match the operational definition of the Lupus Low Disease Activity State (LLDAS)? A case-based construct validity study.

PubMed

Golder, Vera; Huq, Molla; Franklyn, Kate; Calderone, Alicia; Lateef, Aisha; Lau, Chak Sing; Lee, Alfred Lok Hang; Navarra, Sandra Teresa V; Godfrey, Timothy; Oon, Shereen; Hoi, Alberta Yik Bun; Morand, Eric Francis; Nikpour, Mandana

2017-06-01

To evaluate the construct validity of the Lupus Low Disease Activity State (LLDAS), a treatment target in systemic lupus erythematosus (SLE). Fifty SLE case summaries based on real patients were prepared and assessed independently for meeting the operational definition of LLDAS. Fifty international rheumatologists with expertise in SLE, but with no prior involvement in the LLDAS project, responded to a survey in which they were asked to categorize the disease activity state of each case as remission, low, moderate, or high. Agreement between expert opinion and LLDAS was assessed using Cohen's kappa. Overall agreement between expert opinion and the operational definition of LLDAS was 77.96% (95% CI: 76.34-79.58%), with a Cohen's kappa of 0.57 (95% CI: 0.55-0.61). Of the cases (22 of 50) that fulfilled the operational definition of LLDAS, only 5.34% (59 of 22 × 50) of responses classified the cases as moderate/high activity. Of the cases that did not fulfill the operational definition of LLDAS (28 of 50), 35.14% (492 of 28 × 50) of responses classified the cases as remission/low activity. Common reasons for discordance were assignment to remission/low activity of cases with higher corticosteroid doses than defined in LLDAS (prednisolone ≤ 7.5mg) or with SLEDAI-2K >4 due to serological activity (high anti-dsDNA antibody and/or low complement). LLDAS has good construct validity with high overall agreement between the operational definition of LLDAS and expert opinion. Discordance of results suggests that the operational definition of LLDAS is more stringent than expert opinion at defining a low disease activity state. Copyright © 2017 Elsevier Inc. All rights reserved.

A Boolean Consistent Fuzzy Inference System for Diagnosing Diseases and Its Application for Determining Peritonitis Likelihood

PubMed Central

Dragović, Ivana; Turajlić, Nina; Pilčević, Dejan; Petrović, Bratislav; Radojević, Dragan

2015-01-01

Fuzzy inference systems (FIS) enable automated assessment and reasoning in a logically consistent manner akin to the way in which humans reason. However, since no conventional fuzzy set theory is in the Boolean frame, it is proposed that Boolean consistent fuzzy logic should be used in the evaluation of rules. The main distinction of this approach is that it requires the execution of a set of structural transformations before the actual values can be introduced, which can, in certain cases, lead to different results. While a Boolean consistent FIS could be used for establishing the diagnostic criteria for any given disease, in this paper it is applied for determining the likelihood of peritonitis, as the leading complication of peritoneal dialysis (PD). Given that patients could be located far away from healthcare institutions (as peritoneal dialysis is a form of home dialysis) the proposed Boolean consistent FIS would enable patients to easily estimate the likelihood of them having peritonitis (where a high likelihood would suggest that prompt treatment is indicated), when medical experts are not close at hand. PMID:27069500

A model for diagnosing and explaining multiple disorders.

PubMed

Jamieson, P W

1991-08-01

The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.

Explainable expert systems: A research program in information processing

NASA Technical Reports Server (NTRS)

Paris, Cecile L.

1993-01-01

Our work in Explainable Expert Systems (EES) had two goals: to extend and enhance the range of explanations that expert systems can offer, and to ease their maintenance and evolution. As suggested in our proposal, these goals are complementary because they place similar demands on the underlying architecture of the expert system: they both require the knowledge contained in a system to be explicitly represented, in a high-level declarative language and in a modular fashion. With these two goals in mind, the Explainable Expert Systems (EES) framework was designed to remedy limitations to explainability and evolvability that stem from related fundamental flaws in the underlying architecture of current expert systems.

SWAN: An expert system with natural language interface for tactical air capability assessment

NASA Technical Reports Server (NTRS)

Simmons, Robert M.

1987-01-01

SWAN is an expert system and natural language interface for assessing the war fighting capability of Air Force units in Europe. The expert system is an object oriented knowledge based simulation with an alternate worlds facility for performing what-if excursions. Responses from the system take the form of generated text, tables, or graphs. The natural language interface is an expert system in its own right, with a knowledge base and rules which understand how to access external databases, models, or expert systems. The distinguishing feature of the Air Force expert system is its use of meta-knowledge to generate explanations in the frame and procedure based environment.

DELTA: An Expert System for Diesel Electric Locomotive Repair

DTIC Science & Technology

1984-06-01

Rules and Inference Mechanisms. AD-P003 943 The ACE (Automated Cable Expert) Exlpelient: Initial Evaluation of an Expert System for Preventive...tions. The first field prototype expert system, designated CATS -i (Computer-Aided Troubleshooting System - Version 1), was delivered in July 1983 and is

Concepts for image management and communication system for space vehicle health management

NASA Astrophysics Data System (ADS)

Alsafadi, Yasser; Martinez, Ralph

On a space vehicle, the Crew Health Care System will handle minor accidents or illnesses immediately, thereby eliminating the necessity of early mission termination or emergency rescue. For practical reasons, only trained personnel with limited medical experience can be available on space vehicles to render preliminary health care. There is the need to communicate with medical experts at different locations on earth. Interplanetary Image Management and Communication System (IIMACS) will be a bridge between worlds and deliver medical images acquired in space to physicians at different medical centers on earth. This paper discusses the implementation of IIMACS by extending the Global Picture Archiving and Communication System (GPACS) being developed to interconnect medical centers on earth. Furthermore, this paper explores system requirements of IIMACS and different user scenarios. Our conclusion is that IIMACS is feasible using the maturing technology base of GPACS.

Obsolescence Risk Assessment Process Best Practice

NASA Astrophysics Data System (ADS)

Romero Rojo, F. J.; Roy, R.; Kelly, S.

2012-05-01

A component becomes obsolete when it is no longer available from the original manufacturer to the original specification. In long-lifecycle projects, obsolescence has become a major problem as it prevents the maintenance of the system. This is the reason why obsolescence management is now an essential part of the product support activities in sectors such as defence, aerospace, nuclear and railway; where systems need to be supported for several decades. The obsolescence risk assessment for the bill of materials (BoM) is a paramount activity in order to manage obsolescence proactively and cost-effectively. This is the reason why it was necessary to undertake a benchmarking study to develop best practice in this process. A total of 22 obsolescence experts from 13 different organisations/projects from across UK and USA have participated in this study. Their current processes and experience have been taken into account in the development of the best practice process for obsolescence risk assessment. The key factors that have to be analysed in the risk assessment process for each component in the BoM are: number of manufacturers, years to end of life, stock available, consumption rate and operational impact criticality. For the very high risk components, a more detailed analysis is required to inform the decisions regarding the most suitable mitigation strategies. On the contrary, for the low risk components, a fully proactive approach is neither appropriate nor cost effective. Therefore, it is advised for these components that obsolescence issues are dealt with reactively. This process has been validated using case studies with several experts from industry and is currently being implemented by the UK Ministry of Defence as technical guidance within the JSP 886 Volume 7 Part 8.13 standards.

Techniques for capturing expert knowledge - An expert systems/hypertext approach

NASA Technical Reports Server (NTRS)

Lafferty, Larry; Taylor, Greg; Schumann, Robin; Evans, Randy; Koller, Albert M., Jr.

1990-01-01

The knowledge-acquisition strategy developed for the Explosive Hazards Classification (EHC) Expert System is described in which expert systems and hypertext are combined, and broad applications are proposed. The EHC expert system is based on rapid prototyping in which primary knowledge acquisition from experts is not emphasized; the explosive hazards technical bulletin, technical guidance, and minimal interviewing are used to develop the knowledge-based system. Hypertext is used to capture the technical information with respect to four issues including procedural, materials, test, and classification issues. The hypertext display allows the integration of multiple knowlege representations such as clarifications or opinions, and thereby allows the performance of a broad range of tasks on a single machine. Among other recommendations, it is suggested that the integration of hypertext and expert systems makes the resulting synergistic system highly efficient.

[The unwisdom of reason and social injustice].

PubMed

Gillieron, E

1978-01-01

This paper attempts to show that in cases of conflict between a patient and any given agency (e.g. insurance company), the conclusions to which the expert will arrive at are often biassed by the spirit of the law. So when dealing with "responsibility" the law is often stressing a concept which is closer to that of "guilt" (the patient is guilty or the insurance company, or society are guilty). This then brings about an endless conflict where neither party is ready to accept fault. Thus, all measures which could lead to an adequate solution seem to be automatically excluded. Therefore, both parties find themselves in an inevitable deadlock due to the "causal" appreciation of the problem to be solved. The above situation could be avoided if the focus were shifted on results and the means to attain them, instead of trying to establish the origin of a given behaviour. In other words, a "system theory" approach appears to be the best frame of reference for the expert. Such an approach would not only have an impact on the spirit of the law, but also throw a new light on the role of the expert, who would no longer have to seek for more or less fair solutions, but would be able to propose constructive measures liable to solve the conflict.

A New Perspective on Modeling Groundwater-Driven Health Risk With Subjective Information

NASA Astrophysics Data System (ADS)

Ozbek, M. M.

2003-12-01

Fuzzy rule-based systems provide an efficient environment for the modeling of expert information in the context of risk management for groundwater contamination problems. In general, their use in the form of conditional pieces of knowledge, has been either as a tool for synthesizing control laws from data (i.e., conjunction-based models), or in a knowledge representation and reasoning perspective in Artificial Intelligence (i.e., implication-based models), where only the latter may lead to coherence problems (e.g., input data that leads to logical inconsistency when added to the knowledge base). We implement a two-fold extension to an implication-based groundwater risk model (Ozbek and Pinder, 2002) including: 1) the implementation of sufficient conditions for a coherent knowledge base, and 2) the interpolation of expert statements to supplement gaps in knowledge. The original model assumes statements of public health professionals for the characterization of the exposed individual and the relation of dose and pattern of exposure to its carcinogenic effects. We demonstrate the utility of the extended model in that it: 1)identifies inconsistent statements and establishes coherence in the knowledge base, and 2) minimizes the burden of knowledge elicitation from the experts for utilizing existing knowledge in an optimal fashion.ÿÿ

Diagnosis - Using automatic test equipment and artificial intelligence expert systems

NASA Astrophysics Data System (ADS)

Ramsey, J. E., Jr.

Three expert systems (ATEOPS, ATEFEXPERS, and ATEFATLAS), which were created to direct automatic test equipment (ATE), are reviewed. The purpose of the project was to develop an expert system to troubleshoot the converter-programmer power supply card for the F-15 aircraft and have that expert system direct the automatic test equipment. Each expert system uses a different knowledge base or inference engine, basing the testing on the circuit schematic, test requirements document, or ATLAS code. Implementing generalized modules allows the expert systems to be used for any different unit under test. Using converted ATLAS to LISP code allows the expert system to direct any ATE using ATLAS. The constraint propagated frame system allows for the expansion of control by creating the ATLAS code, checking the code for good software engineering techniques, directing the ATE, and changing the test sequence as needed (planning).

Expert Systems in Education and Training: Automated Job Aids or Sophisticated Instructional Media?

ERIC Educational Resources Information Center

Romiszowski, Alexander J.

1987-01-01

Describes the current status and limitations of expert systems, and explores the possible applications of such systems in education and training. The use of expert systems as tutors, as job aids, and as a vehicle for students to develop their own expert systems on specific topics are discussed. (40 references) (CLB)

Expert patient illness narratives as a teaching methodology: A mixed method study of student nurses satisfaction.

PubMed

Feijoo-Cid, Maria; Moriña, David; Gómez-Ibáñez, Rebeca; Leyva-Moral, Juan M

2017-03-01

To evaluate nursing students' satisfaction with Expert Patient Illness Narratives as a teaching and learning methodology based on patient involvement. Mixed methods were used in this study: online survey with quantitative and qualitative items designed by researchers. Sixty-four nursing students of the Universitat Autònoma de Barcelona, attending a Medical Anthropology elective course. Women more frequently considered that the new learning methodology was useful in developing the competency "to reason to reason the presence of the triad Health-Illness-Care in all the groups, societies and historical moments" (p-value=0.02) and in that it was consolidated as a learning outcome (p-value=0.022). On the other hand, men considered that this methodology facilitated the development of critical thinking (p=0.01) and the ability to identify normalized or deviant care situations (p=0.007). Students recognized the value of Expert Patient Illness Narratives in their nursing training as a way to acquire new nursing skills and broaden previously acquired knowledge. This educational innovation improved nursing skills and provided a different and richer perspective of humanization of care. The results of the present study demonstrate that nursing students found Expert Patient Illness Narratives satisfactory as a learning and teaching methodology, and reported improvement in different areas of their training and also the integration of new knowledge, meaning, theory applicability, as well las critical and reflective thinking. Involvement of patients as storytellers also provides a new humanizing perspective of care. Nonetheless, further studies of Expert Patient Illness Narratives are needed in order to improve its benefits as a teaching and learning methodology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

NASA Technical Reports Server (NTRS)

1986-01-01

The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

Validation of undergraduate medical student script concordance test (SCT) scores on the clinical assessment of the acute abdomen.

PubMed

Goos, Matthias; Schubach, Fabian; Seifert, Gabriel; Boeker, Martin

2016-08-17

Health professionals often manage medical problems in critical situations under time pressure and on the basis of vague information. In recent years, dual process theory has provided a framework of cognitive processes to assist students in developing clinical reasoning skills critical especially in surgery due to the high workload and the elevated stress levels. However, clinical reasoning skills can be observed only indirectly and the corresponding constructs are difficult to measure in order to assess student performance. The script concordance test has been established in this field. A number of studies suggest that the test delivers a valid assessment of clinical reasoning. However, different scoring methods have been suggested. They reflect different interpretations of the underlying construct. In this work we want to shed light on the theoretical framework of script theory and give an idea of script concordance testing. We constructed a script concordance test in the clinical context of "acute abdomen" and compared previously proposed scores with regard to their validity. A test comprising 52 items in 18 clinical scenarios was developed, revised along the guidelines and administered to 56 4(th) and 5(th) year medical students at the end of a blended-learning seminar. We scored the answers using five different scoring methods (distance (2×), aggregate (2×), single best answer) and compared the scoring keys, the resulting final scores and Cronbach's α after normalization of the raw scores. All scores except the single best answers calculation achieved acceptable reliability scores (>= 0.75), as measured by Cronbach's α. Students were clearly distinguishable from the experts, whose results were set to a mean of 80 and SD of 5 by the normalization process. With the two aggregate scoring methods, the students' means values were between 62.5 (AGGPEN) and 63.9 (AGG) equivalent to about three expert SD below the experts' mean value (Cronbach's α : 0.76 (AGGPEN) and 0.75 (AGG)). With the two distance scoring methods the students' mean was between 62.8 (DMODE) and 66.8 (DMEAN) equivalent to about two expert SD below the experts' mean value (Cronbach's α: 0.77 (DMODE) and 0.79 (DMEAN)). In this study the single best answer (SBA) scoring key yielded the worst psychometric results (Cronbach's α: 0.68). Assuming the psychometric properties of the script concordance test scores are valid, then clinical reasoning skills can be measured reliably with different scoring keys in the SCT presented here. Psychometrically, the distance methods seem to be superior, wherein inherent statistical properties of the scales might play a significant role. For methodological reasons, the aggregate methods can also be used. Despite the limitations and complexity of the underlying scoring process and the calculation of reliability, we advocate for SCT because it allows a new perspective on the measurement and teaching of cognitive skills.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Knowledge translation from continuing education to physiotherapy practice in classifying patients with low back pain.

PubMed

Karvonen, Eira; Paatelma, Markku; Kesonen, Jukka-Pekka; Heinonen, Ari O

2015-05-01

Physical therapists have used continuing education as a method of improving their skills in conducting clinical examination of patients with low back pain (LBP). The purpose of this study was to evaluate how well the pathoanatomical classification of patients in acute or subacute LBP can be learned and applied through a continuing education format. The patients were seen in a direct access setting. The study was carried out in a large health-care center in Finland. The analysis included a total of 57 patient evaluations generated by six physical therapists on patients with LBP. We analyzed the consistency and level of agreement of the six physiotherapists' (PTs) diagnostic decisions, who participated in a 5-day, intensive continuing education session and also compared those with the diagnostic opinions of two expert physical therapists, who were blind to the original diagnostic decisions. Evaluation of the physical therapists' clinical examination of the patients was conducted by the two experts, in order to determine the accuracy and percentage agreement of the pathoanatomical diagnoses. The percentage of agreement between the experts and PTs was 72-77%. The overall inter-examiner reliability (kappa coefficient) for the subgroup classification between the six PTs and two experts was 0.63 [95% confidence interval (CI): 0.47-0.77], indicating good agreement between the PTs and the two experts. The overall inter-examiner reliability between the two experts was 0.63 (0.49-0.77) indicating good level of agreement. Our results indicate that PTs' were able to apply their continuing education training to clinical reasoning and make consistently accurate pathoanatomic based diagnostic decisions for patients with LBP. This would suggest that continuing education short-courses provide a reasonable format for knowledge translation (KT) by which physical therapists can learn and apply new information related to the examination and differential diagnosis of patients in acute or subacute LBP.

Assessing clinical reasoning (ASCLIRE): Instrument development and validation.

PubMed

Kunina-Habenicht, Olga; Hautz, Wolf E; Knigge, Michel; Spies, Claudia; Ahlers, Olaf

2015-12-01

Clinical reasoning is an essential competency in medical education. This study aimed at developing and validating a test to assess diagnostic accuracy, collected information, and diagnostic decision time in clinical reasoning. A norm-referenced computer-based test for the assessment of clinical reasoning (ASCLIRE) was developed, integrating the entire clinical decision process. In a cross-sectional study participants were asked to choose as many diagnostic measures as they deemed necessary to diagnose the underlying disease of six different cases with acute or sub-acute dyspnea and provide a diagnosis. 283 students and 20 content experts participated. In addition to diagnostic accuracy, respective decision time and number of used relevant diagnostic measures were documented as distinct performance indicators. The empirical structure of the test was investigated using a structural equation modeling approach. Experts showed higher accuracy rates and lower decision times than students. In a cross-sectional comparison, the diagnostic accuracy of students improved with the year of study. Wrong diagnoses provided by our sample were comparable to wrong diagnoses in practice. We found an excellent fit for a model with three latent factors-diagnostic accuracy, decision time, and choice of relevant diagnostic information-with diagnostic accuracy showing no significant correlation with decision time. ASCLIRE considers decision time as an important performance indicator beneath diagnostic accuracy and provides evidence that clinical reasoning is a complex ability comprising diagnostic accuracy, decision time, and choice of relevant diagnostic information as three partly correlated but still distinct aspects.

Reasoning over taxonomic change: exploring alignments for the Perelleschus use case.

PubMed

Franz, Nico M; Chen, Mingmin; Yu, Shizhuo; Kianmajd, Parisa; Bowers, Shawn; Ludäscher, Bertram

2015-01-01

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted Region Connection Calculus articulations (e.g., congruence, proper inclusion, overlap, or exclusion). An Open Source reasoning toolkit is used to analyze 13 paired Perelleschus taxonomy alignments under heterogeneous constraints and interpretations. The reasoning workflow optimizes the logical consistency and expressiveness of the input and infers the set of maximally informative relations among the entailed taxonomic concepts. The latter are then used to produce merge visualizations that represent all congruent and non-congruent taxonomic elements among the aligned input trees. In this small use case with 6-53 input concepts per alignment, the information gained through the reasoning process is on average one order of magnitude greater than in the input. The approach offers scalable solutions for tracking provenance among succeeding taxonomic perspectives that may have differential biases in naming conventions, phylogenetic resolution, ingroup and outgroup sampling, or ostensive (member-referencing) versus intensional (property-referencing) concepts and articulations.

Learning clinical reasoning.

PubMed

Pinnock, Ralph; Welch, Paul

2014-04-01

Errors in clinical reasoning continue to account for significant morbidity and mortality, despite evidence-based guidelines and improved technology. Experts in clinical reasoning often use unconscious cognitive processes that they are not aware of unless they explain how they are thinking. Understanding the intuitive and analytical thinking processes provides a guide for instruction. How knowledge is stored is critical to expertise in clinical reasoning. Curricula should be designed so that trainees store knowledge in a way that is clinically relevant. Competence in clinical reasoning is acquired by supervised practice with effective feedback. Clinicians must recognise the common errors in clinical reasoning and how to avoid them. Trainees can learn clinical reasoning effectively in everyday practice if teachers provide guidance on the cognitive processes involved in making diagnostic decisions. © 2013 The Authors. Journal of Paediatrics and Child Health © 2013 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Knowledge-based support for the participatory design and implementation of shift systems.

PubMed

Gissel, A; Knauth, P

1998-01-01

This study developed a knowledge-based software system to support the participatory design and implementation of shift systems as a joint planning process including shift workers, the workers' committee, and management. The system was developed using a model-based approach. During the 1st phase, group discussions were repeatedly conducted with 2 experts. Thereafter a structure model of the process was generated and subsequently refined by the experts in additional semistructured interviews. Next, a factual knowledge base of 1713 relevant studies was collected on the effects of shift work. Finally, a prototype of the knowledge-based system was tested on 12 case studies. During the first 2 phases of the system, important basic information about the tasks to be carried out is provided for the user. During the 3rd phase this approach uses the problem-solving method of case-based reasoning to determine a shift rota which has already proved successful in other applications. It can then be modified in the 4th phase according to the shift workers' preferences. The last 2 phases support the final testing and evaluation of the system. The application of this system has shown that it is possible to obtain shift rotas suitable to actual problems and representative of good ergonomic solutions. A knowledge-based approach seems to provide valuable support for the complex task of designing and implementing a new shift system. The separation of the task into several phases, the provision of information at all stages, and the integration of all parties concerned seem to be essential factors for the success of the application.

A neural network architecture for implementation of expert systems for real time monitoring

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.

1991-01-01

Since neural networks have the advantages of massive parallelism and simple architecture, they are good tools for implementing real time expert systems. In a rule based expert system, the antecedents of rules are in the conjunctive or disjunctive form. We constructed a multilayer feedforward type network in which neurons represent AND or OR operations of rules. Further, we developed a translator which can automatically map a given rule base into the network. Also, we proposed a new and powerful yet flexible architecture that combines the advantages of both fuzzy expert systems and neural networks. This architecture uses the fuzzy logic concepts to separate input data domains into several smaller and overlapped regions. Rule-based expert systems for time critical applications using neural networks, the automated implementation of rule-based expert systems with neural nets, and fuzzy expert systems vs. neural nets are covered.

What Is An Expert System? ERIC Digest.

ERIC Educational Resources Information Center

Boss, Richard W.

This digest describes and defines the various components of an expert system, e.g., a computerized tool designed to enhance the quality and availability of knowledge required by decision makers. It is noted that expert systems differ from conventional applications software in the following areas: (1) the existence of the expert systems shell, or…

Expert Systems: Implications for the Diagnosis and Treatment of Learning Disabilities.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Lubke, Margaret M.

1988-01-01

The article examines characteristics and present or potential applications of expert systems technology for diagnosis and treatment of learning disabilities. Preliminary findings indicate that expert systems can perform as well as humans in specific areas, and that the process of organizing knowledge bases for expert systems helps clarify existing…

[Recommendations for terminating child custody--reasons and grounds in 30 expert decisions].

PubMed

Klosinski, G; Karle, M

1996-11-01

In a retrospective analysis 30 expert opinions on the right of visitation, which recommend the exclusion of this right for the non-custodial parent, are evaluated. These cases represent 23% of the expert opinions concerning the right of visitation that have been given by the department of Child and Adolescent Psychiatry of the University of Tübingen between 1991 and 1994. Focusing on the decisive argument for the expert to exclude the right of visitation, it became apparent that in 40% of the cases the will of the child was the determining factor, followed by sustained tension between the parents in 33% of the cases. Emotional neglect, (continuous) abuse and maltreatment (12%) as well as offences against the clause of good behaviour (Wohlverhaltensklausel) were of significant smaller influence on the decision. And although 61% of the children have been classified as psychological disturbed, only in 5% of the cases this diagnosis was of importance.

[Problems in expert assessment in child custody cases according to sections 1666, 1666a BGB in the controversy between control and assistance].

PubMed

Rüth, U

1998-09-01

The restriction of parental rights includes not only legal but also therapeutic aspects. The therapeutic aspects refer first to the child's disorder and then to its resulting needs. Furthermore a restriction of parental rights could be necessary for therapeutic reasons when the parents' reaction to reality is insufficient, usually caused by parental psychiatric disorders. The expert's counsel should facilitate the communication with disturbed parents thus engendering an improved reality-insight by the parents. Successful helping strategies can thus be made workable. The expert, the judge and the local authority social services should mutually respect specifically defined role-functions. The communication barriers between parents and helpers can only this way be partially resolved. The expert's evidence requires a high professional competence and responsibility and goes over and above the professional contribution from family therapy.

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert

PubMed Central

Schmidt, Henk G.; Rikers, Remy M. J. P.; Custers, Eugene J. F. M.; Splinter, Ted A. W.; van Saase, Jan L. C. M.

2010-01-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices’ decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases. PMID:20354726

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert.

PubMed

Mamede, Sílvia; Schmidt, Henk G; Rikers, Remy M J P; Custers, Eugene J F M; Splinter, Ted A W; van Saase, Jan L C M

2010-11-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices' decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases.

Is the French criminal psychiatric assessment in crisis?

PubMed

Guivarch, J; Piercecchi-Marti, M-D; Glezer, D; Murdymootoo, V; Chabannes, J-M; Poinso, F

The criminal psychiatric assessment in France seems to be facing growing criticism related to disagreements between experts and, on the other hand, a lack of interest of psychiatrists for the assessment. We start by explaining the current framework of the criminal psychiatric assessment in France, which differs from the assessment used in English-speaking countries, where Roman law applies. Then, we will describe the disagreements through a literature review and two clinical vignettes. Finally, we will try to understand the causes of discrepancies between experts and the reasons for a supposed lack of interest of the psychiatrists for the expertise. For this, we conducted a survey among the psychiatric experts. We individually questioned experts on the discrepancies and on their awareness of the expertise. We found that 75% of the experts we surveyed had already faced the divergent opinion of a colleague. In addition, the experts were divided on their conclusions related to the fictional scenario we gave them for an a priori assessment (a person with schizophrenia who was accused of murder), particularly in the specific contexts that we submitted to them. The main cause of disagreement between experts was the various schools of thought that influence the psychiatric experts in the forensic discussion and, therefore, the conclusions of a case. Moreover, the experts believed that the decrease in the number of psychiatric experts could be attributed to the adverse financial situation of the assessment, the considerable workload required, and the extensive responsibility that falls on the expert. Calling on a team of forensic experts to perform assessments seems to be the first solution to this crisis. Furthermore, if the experts were better compensated for the assessments, more people would want to undertake this work. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structural interpretation of seismic data and inherent uncertainties

NASA Astrophysics Data System (ADS)

Bond, Clare

2013-04-01

Geoscience is perhaps unique in its reliance on incomplete datasets and building knowledge from their interpretation. This interpretation basis for the science is fundamental at all levels; from creation of a geological map to interpretation of remotely sensed data. To teach and understand better the uncertainties in dealing with incomplete data we need to understand the strategies individual practitioners deploy that make them effective interpreters. The nature of interpretation is such that the interpreter needs to use their cognitive ability in the analysis of the data to propose a sensible solution in their final output that is both consistent not only with the original data but also with other knowledge and understanding. In a series of experiments Bond et al. (2007, 2008, 2011, 2012) investigated the strategies and pitfalls of expert and non-expert interpretation of seismic images. These studies focused on large numbers of participants to provide a statistically sound basis for analysis of the results. The outcome of these experiments showed that a wide variety of conceptual models were applied to single seismic datasets. Highlighting not only spatial variations in fault placements, but whether interpreters thought they existed at all, or had the same sense of movement. Further, statistical analysis suggests that the strategies an interpreter employs are more important than expert knowledge per se in developing successful interpretations. Experts are successful because of their application of these techniques. In a new set of experiments a small number of experts are focused on to determine how they use their cognitive and reasoning skills, in the interpretation of 2D seismic profiles. Live video and practitioner commentary were used to track the evolving interpretation and to gain insight on their decision processes. The outputs of the study allow us to create an educational resource of expert interpretation through online video footage and commentary with associated further interpretation and analysis of the techniques and strategies employed. This resource will be of use to undergraduate, post-graduate, industry and academic professionals seeking to improve their seismic interpretation skills, develop reasoning strategies for dealing with incomplete datasets, and for assessing the uncertainty in these interpretations. Bond, C.E. et al. (2012). 'What makes an expert effective at interpreting seismic images?' Geology, 40, 75-78. Bond, C. E. et al. (2011). 'When there isn't a right answer: interpretation and reasoning, key skills for 21st century geoscience'. International Journal of Science Education, 33, 629-652. Bond, C. E. et al. (2008). 'Structural models: Optimizing risk analysis by understanding conceptual uncertainty'. First Break, 26, 65-71. Bond, C. E. et al., (2007). 'What do you think this is?: "Conceptual uncertainty" In geoscience interpretation'. GSA Today, 17, 4-10.

Design of an Ada expert system shell for the VHSIC avionic modular flight processor

NASA Technical Reports Server (NTRS)

Fanning, F. Jesse

1992-01-01

The Embedded Computer System Expert System Shell (ES Shell) is an Ada-based expert system shell developed at the Avionics Laboratory for use on the VHSIC Avionic Modular Processor (VAMP) running under the Ada Avionics Real-Time Software (AARTS) Operating System. The ES Shell provides the interface between the expert system and the avionics environment, and controls execution of the expert system. Testing of the ES Shell in the Avionics Laboratory's Integrated Test Bed (ITB) has demonstrated its ability to control a non-deterministic software application executing on the VAMP's which can control the ITB's real-time closed-loop aircraft simulation. The results of these tests and the conclusions reached in the design and development of the ES Shell have played an important role in the formulation of the requirements for a production-quality expert system inference engine, an ingredient necessary for the successful use of expert systems on the VAMP embedded avionic flight processor.

The need for a comprehensive expert system development methodology

NASA Technical Reports Server (NTRS)

Baumert, John; Critchfield, Anna; Leavitt, Karen

1988-01-01

In a traditional software development environment, the introduction of standardized approaches has led to higher quality, maintainable products on the technical side and greater visibility into the status of the effort on the management side. This study examined expert system development to determine whether it differed enough from traditional systems to warrant a reevaluation of current software development methodologies. Its purpose was to identify areas of similarity with traditional software development and areas requiring tailoring to the unique needs of expert systems. A second purpose was to determine whether existing expert system development methodologies meet the needs of expert system development, management, and maintenance personnel. The study consisted of a literature search and personal interviews. It was determined that existing methodologies and approaches to developing expert systems are not comprehensive nor are they easily applied, especially to cradle to grave system development. As a result, requirements were derived for an expert system development methodology and an initial annotated outline derived for such a methodology.

Validation of an expert system intended for research in distributed artificial intelligence

NASA Technical Reports Server (NTRS)

Grossner, C.; Lyons, J.; Radhakrishnan, T.

1991-01-01

The expert system discussed in this paper is designed to function as a testbed for research on cooperating expert systems. Cooperating expert systems are members of an organization which dictates the manner in which the expert systems will interact when solving a problem. The Blackbox Expert described in this paper has been constructed using the C Language Integrated Production System (CLIPS), C++, and X windowing environment. CLIPS is embedded in a C++ program which provides objects that are used to maintain the state of the Blackbox puzzle. These objects are accessed by CLIPS rules through user-defined functions calls. The performance of the Blackbox Expert is validated by experimentation. A group of people are asked to solve a set of test cases for the Blackbox puzzle. A metric has been devised which evaluates the 'correctness' of a solution proposed for a test case of Blackbox. Using this metric and the solutions proposed by the humans, each person receives a rating for their ability to solve the Blackbox puzzle. The Blackbox Expert solves the same set of test cases and is assigned a rating for its ability. Then the rating obtained by the Blackbox Expert is compared with the ratings of the people, thus establishing the skill level of our expert system.

Photolithography diagnostic expert systems: a systematic approach to problem solving in a wafer fabrication facility

NASA Astrophysics Data System (ADS)

Weatherwax Scott, Caroline; Tsareff, Christopher R.

1990-06-01

One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity and throughput. Engineers must work continuously toward this goal in addition to performing sustaining and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources. One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge based computer programs designed to lead the user through the analysis and solution of a problem. Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to provide a systematic approach to process problem solving. This systematic approach was achieved by documenting cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the knowledge base of the expert system which is stored in the computer. The systems also include the problem solving methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert systems to solve many process problems without engineering assistance. The systems also facilitate the collection of appropriate data to assist engineering in solving unanticipated problems. Currently, several expert systems have been implemented to cover all aspects of the photolithography process. The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement an expert system diagnostic environment throughout the wafer fabrication facility. In this paper, the systems' construction is described, including knowledge acquisition, rule construction, knowledge refinement, testing, and evaluation. The roles played by the process engineering expert and the knowledge engineer are discussed. The features of the systems are shown, particularly the interactive quality of the consultations and the ease of system use.

MOORE: A prototype expert system for diagnosing spacecraft problems

NASA Technical Reports Server (NTRS)

Howlin, Katherine; Weissert, Jerry; Krantz, Kerry

1988-01-01

MOORE is a rule-based, prototype expert system that assists in diagnosing operational Tracking and Data Relay Satellite (TDRS) problems. It is intended to assist spacecraft engineers at the TDRS ground terminal in trouble shooting problems that are not readily solved with routine procedures, and without expert counsel. An additional goal of the prototype system is to develop in-house expert system and knowledge engineering skills. The prototype system diagnoses antenna pointing and earth pointing problems that may occur within the TDRS Attitude Control System (ACS). Plans include expansion to fault isolation of problems in the most critical subsystems of the TDRS spacecraft. Long term benefits are anticipated with use of an expert system during future TDRS programs with increased mission support time, reduced problem solving time, and retained expert knowledge and experience. Phase 2 of the project is intended to provide NASA the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking Data Relay Satellite. Phase 2 also envisions addressing two unexplored applications for expert systems, spacecraft integration and tests (I and T) and support to launch activities. The concept, goals, domain, tools, knowledge acquisition, developmental approach, and design of the expert system. It will explain how NASA obtained the knowledge and capability to develop the system in-house without assistance from outside consultants. Future plans will also be presented.

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacAllister, D.J.; Day, R.; McCormack, M.D.

This paper gives an overview of a major integrated oil company`s experience with artificial intelligence (AI) over the last 5 years, with an emphasis on expert systems. The authors chronicle the development of an AI group, including details on development tool selection, project selection strategies, potential pitfalls, and descriptions of several completed expert systems. Small expert systems produced by teams of petroleum technology experts and experienced expert system developers that are focused in well-defined technical areas have produced substantial benefits and accelerated petroleum technology transfer.

The GIS map coloring support decision-making system based on case-based reasoning and simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Deng, Shuang; Xiang, Wenting; Tian, Yangge

2009-10-01

Map coloring is a hard task even to the experienced map experts. In the GIS project, usually need to color map according to the customer, which make the work more complex. With the development of GIS, more and more programmers join the project team, which lack the training of cartology, their coloring map are harder to meet the requirements of customer. From the experience, customers with similar background usually have similar tastes for coloring map. So, we developed a GIS color scheme decision-making system which can select color schemes of similar customers from case base for customers to select and adjust. The system is a BS/CS mixed system, the client side use JSP and make it possible for the system developers to go on remote calling of the colors scheme cases in the database server and communicate with customers. Different with general case-based reasoning, even the customers are very similar, their selection may have difference, it is hard to provide a "best" option. So, we select the Simulated Annealing Algorithm (SAA) to arrange the emergence order of different color schemes. Customers can also dynamically adjust certain features colors based on existing case. The result shows that the system can facilitate the communication between the designers and the customers and improve the quality and efficiency of coloring map.

An expert systems approach to automated fault management in a regenerative life support subsystem

NASA Technical Reports Server (NTRS)

Malin, J. T.; Lance, N., Jr.

1986-01-01

This paper describes FIXER, a prototype expert system for automated fault management in a regenerative life support subsystem typical of Space Station applications. The development project provided an evaluation of the use of expert systems technology to enhance controller functions in space subsystems. The software development approach permitted evaluation of the effectiveness of direct involvement of the expert in design and development. The approach also permitted intensive observation of the knowledge and methods of the expert. This paper describes the development of the prototype expert system and presents results of the evaluation.

Evolution of a research prototype expert system for endemic populations of mountain pine beetle in lodgepole pine forests

Treesearch

Dale L. Bartos; Kent B. Downing

1989-01-01

A knowledge acquisition program was written to aid in obtaining knowledge from the experts concerning endemic populations of mountain pine beetle in lodgepole pine forest. An application expert system is then automatically generated by the knowledge acquisition program that contains the codified base of expert knowledge. Data can then be entered into the expert system...

From Novice to Expert: Problem Solving in ICD-10-PCS Procedural Coding

PubMed Central

Rousse, Justin Thomas

2013-01-01

The benefits of converting to ICD-10-CM/PCS have been well documented in recent years. One of the greatest challenges in the conversion, however, is how to train the workforce in the code sets. The International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS) has been described as a language requiring higher-level reasoning skills because of the system's increased granularity. Training and problem-solving strategies required for correct procedural coding are unclear. The objective of this article is to propose that the acquisition of rule-based logic will need to be augmented with self-evaluative and critical thinking. Awareness of how this process works is helpful for established coders as well as for a new generation of coders who will master the complexities of the system. PMID:23861674

Simple methods of exploiting the underlying structure of rule-based systems

NASA Technical Reports Server (NTRS)

Hendler, James

1986-01-01

Much recent work in the field of expert systems research has aimed at exploiting the underlying structures of the rule base for reasons of analysis. Such techniques as Petri-nets and GAGs have been proposed as representational structures that will allow complete analysis. Much has been made of proving isomorphisms between the rule bases and the mechanisms, and in examining the theoretical power of this analysis. In this paper we describe some early work in a new system which has much simpler (and thus, one hopes, more easily achieved) aims and less formality. The technique being examined is a very simple one: OPS5 programs are analyzed in a purely syntactic way and a FSA description is generated. In this paper we describe the technique and some user interface tools which exploit this structure.

Using C to build a satellite scheduling expert system: Examples from the Explorer platform planning system

NASA Technical Reports Server (NTRS)

Mclean, David R.; Tuchman, Alan; Potter, William J.

1991-01-01

Recently, many expert systems were developed in a LISP environment and then ported to the real world C environment before the final system is delivered. This situation may require that the entire system be completely rewritten in C and may actually result in a system which is put together as quickly as possible with little regard for maintainability and further evolution. With the introduction of high performance UNIX and X-windows based workstations, a great deal of the advantages of developing a first system in the LISP environment have become questionable. A C-based AI development effort is described which is based on a software tools approach with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching and a blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May 1987 and will be used for operations scheduling of the Explorer Platform in November 1991.

Operation and Structure of an Artificial Intelligence Expert Consultative System for Reading and Learning.

ERIC Educational Resources Information Center

Balajthy, Ernest

1989-01-01

The article examines decision-making expert systems and discusses their implications for diagnosis and prescription of reading difficulties. A detailed description of how a reading diagnostic expert system might operate to aid classroom teachers is followed by a discussion of advantages and limitations of expert systems for educational use.…

Expert database system for quality control

NASA Astrophysics Data System (ADS)

Wang, Anne J.; Li, Zhi-Cheng

1993-09-01

There are more competitors today. Markets are not homogeneous they are fragmented into increasingly focused niches requiring greater flexibility in the product mix shorter manufacturing production runs and above allhigher quality. In this paper the author identified a real-time expert system as a way to improve plantwide quality management. The quality control expert database system (QCEDS) by integrating knowledge of experts in operations quality management and computer systems use all information relevant to quality managementfacts as well as rulesto determine if a product meets quality standards. Keywords: expert system quality control data base

Parallel processing and expert systems

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Lau, Sonie

1991-01-01

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited.